Source: raw/reddit-1um5er6.md (r/Anthropic surfacing, score 380) + ai-research/openai-gpt-5-6-sol-preview.md, verified against the official primary source https://openai.com/index/previewing-gpt-5-6-sol/ and the OpenAI Help Center (help.openai.com/en/articles/20001325). 2026-07-10 GA-launch refresh: raw/A_Model_Explosion_-_GPT_5.6_Sol_Grok_4.5_and_Meta_Muse_Rewrite_the_Rules.md (cross-model benchmark roundup) + raw/I_Tested_GPT_5.6_Sol_vs_Fable_5.What_You_Need_To_Know..md (single-tester side-by-side agentic build tests) + raw/AI_News-_GPT-5.6_and_the_new_Super_App_are_a_Massive_Leap.md (Matt Wolfe weekly AI news, GA-day hands-on). 2026-09-29: long-context pricing and latency from the Epoch Brief of 2026-09-12 (raw/newsletter-epoch-ai-c590b192b4.md). 2026-09-29, second pass: post-launch price cuts from OpenAI’s GPT-6 Sol/Luna page (ai-research/openai-gpt-6-sol-and-luna-announcement-2026-09.md), The AI Daily Brief, Matt Wolfe and Matthew Berman; ChatGPT Work detail from Lenny’s Podcast with OpenAI’s Tara Seshan.
Superseded by GPT-6 (2026-09-22). OpenAI replaced GPT-5.6 Sol and Luna with GPT-6 Sol (10) and GPT-6 Luna (0.50) on 2026-09-22, after GPT-6 Astra (50) on 2026-09-03. There is no GPT-6 Terra. For current routing, see Luna). This article stays as the record of the GPT-5.6 generation.
OpenAI’s GPT-5.6 ships as a three-tier family instead of one model — Sol (flagship), Terra (balanced), and Luna (high-volume, cheapest) — announced in limited preview in late June 2026^[inferred — multiple secondary reports date it June 2026; the official-page extract does not state a date] and surfaced on r/Anthropic on 2026-07-03 as “competition for Fable 5.” The practical story for anyone routing spend across models is the pricing spread: Sol lands at 30 per 1M tokens — half of Claude Fable 5’s 50 on input, 40% cheaper on output — while Terra and Luna open two cheaper rungs inside the same generation. This article treats GPT-5.6 as a competitor datapoint for model/cost routing, not as an endorsement.
Update (2026-07-10): GPT-5.6 exited preview and reached general availability on 2026-07-09, launching alongside a unified ChatGPT Work app that merges Codex, ChatGPT, and the Atlas browser into one surface. See the GA-week sections below for benchmark deltas, a single-tester head-to-head against Fable 5, the new app architecture, and a safety-relevant update to the jailbreak-resistance claim in this article’s original safeguard bullet.
Key Takeaways
- Three tiers, per-1M-token pricing (VERIFIED against the official OpenAI page and Help Center): Sol
$5 / $30, Terra$2.50 / $15, Luna$1 / $6(input / output). Terra is exactly half of Sol; Luna is the new low-cost rung. - “Sol Ultra” is a mode, not a tier. The Reddit stub labeled the 30 price “Sol Ultra.” Corrected on verification:
$5/$30is the price of Sol.maxandultraare reasoning-effort settings (ultraspins up subagents); “GPT-5.6 Sol Ultra” is Sol run at the top effort level, which reportedly posts the top Terminal-Bench score^[secondary: DataCamp, explainx — not in the official-page extract]. - Sol matches GPT-5.5’s rate card exactly (30) — the generational value is in the cheaper Terra/Luna rungs, not a top-tier price cut^[secondary: eesel, finout, VentureBeat].
- The naming drops “mini”/“nano.” OpenAI reportedly reframed the family around use case rather than model size; there is no mini/nano variant and no “Pro” tier yet^[secondary: VentureBeat, eesel].
- More predictable prompt caching (5.6+): explicit cache breakpoints, 30-minute minimum cache life, cache writes billed at 1.25x the uncached input rate, cache reads keep the 90% discount (official).
- Cyber-forward: Sol is OpenAI’s “most capable model yet for cybersecurity” — on ExploitBench, competitive with Anthropic’s Mythos Preview using only ~1/3 the output tokens; on UC-Berkeley-built ExploitGym all three tiers improve with more reasoning (official). This is the same capability class that triggers Anthropic’s Mythos-family gating.
- Availability is gated. Preview is API + Codex only, restricted to ~20 organizations whose participation was cleared under a US-government frontier-model review; broad ChatGPT access has no firm date^[secondary: Handy AI, VentureBeat] — see Mythos 5 federal story.
- Speed play: GPT-5.6 Sol on Cerebras at up to 750 tokens/sec in July, initially for select customers (official).
- GA’d 2026-07-09 — no longer preview-gated. GPT-5.6 (Sol/Terra/Luna) left the ~20-org preview and reached general availability the same week, launching inside a new unified ChatGPT Work app (Codex + ChatGPT + Atlas browser merged into one surface — see below).
- The GA benchmark story is richer but mixed, not a clean Sol-beats-Fable sweep. Sol leads some measures (Buybench top-4 sweep, Artificial Analysis Coding Index 80 vs Fable’s 77, Agent’s Last Exam 54% XH vs Fable’s 45% max) and trails on others (GDPval Elo, SWE-Marathon — where Fable 5 trails and Grok 4.5 actually leads). See the GA benchmark roundup below for the full picture and caveats.
- UK AI Security Institute found a universal jailbreak within hours of GA release. Flagged as a direct update to this article’s earlier “700,000+ GPU-hours of red-teaming for universal jailbreaks” safeguard claim — see the contradiction callout in Benchmarks & Safeguards.
Pricing
GPT-5.6 tiers (VERIFIED — official OpenAI page + Help Center), with the closest wiki-tracked model neighbors for routing context:
| Model | Input /1M | Output /1M | Role / notes |
|---|---|---|---|
GPT-5.6 Sol (gpt-5.6-sol) | $5.00 | $30.00 | OpenAI flagship; frontier coding / cyber / agentic. max + ultra effort modes. |
GPT-5.6 Terra (gpt-5.6-terra) | $2.50 | $15.00 | Balanced production; exactly half of Sol. |
GPT-5.6 Luna (gpt-5.6-luna) | $1.00 | $6.00 | High-volume / cheap; classification, routing, moderation, summarization. |
| Claude Fable 5 | $10.00 | $50.00 | Anthropic Mythos-class flagship (the comparison anchor). |
| Claude Opus 4.8 | $5.00 | $25.00 | Fable’s safeguard-fallback model; Sol matches it on input, undercuts on output. |
| Claude Sonnet 5 | $3.00 | $15.00 | Std pricing post-Aug-31 (10 promo before); ties Terra on output. |
| GLM-5.2 (Z.ai) | ~$1.40 | ~$4.40 | Open-weight value tier; undercuts even Luna^[creator-cited/approximate; corroborated by VentureBeat’s comparison table]. |
Long-context surcharge (added 2026-09-29). Per the Epoch Brief of 2026-09-12, GPT-5.6 prices rise past 272k input tokens, while Claude 5 prices stay fixed as context grows. The flat rates in the table above apply below that threshold. ^[inferred] See Open Questions for Epoch’s latency finding.
Price cuts after launch (added 2026-09-29). The table above is GPT-5.6’s launch list price, verified in July. OpenAI later cut it:
- Luna and Terra first. The AI Daily Brief, in an episode from late August, said “costs for Luna and Terra were already cut late last month.” Matthew Berman refers to GPT-5.6 Luna’s “80% price drop,” which matches 6 → 1.20. Terra’s new price is not given in any source here.
- Then Sol. The AI Daily Brief: Sol over the API “will now cost 20 per million output tokens, down from 30.” Matt Wolfe reported it as Sol being “20% cheaper for the next three months,” i.e. a time-limited promotion.
- OpenAI’s own label is “promotional pricing.” OpenAI’s GPT-6 Sol/Luna page lists GPT-5.6 Sol at 20 and GPT-5.6 Luna at 1.20, and cuts GPT-6 prices 50% “compared with their GPT‑5.6 promotional pricing.” That is why Matt Wolfe’s news video on the GPT-6 Sol launch gives GPT-5.6 Sol as “20 output” and Luna as “20 cents… and a buck 20”: he was quoting the promotional prices, not contradicting the launch prices above.
Caching detail (5.6+, official): explicit cache breakpoints, 30-min minimum cache life, cache writes at 1.25x uncached input, cache reads at the 90% discount. For agent loops that reuse system prompts and tool schemas, the caching terms move total cost as much as the sticker rate — especially in ultra mode where subagent calls multiply.
What It Means for Model & Cost Routing
The competitor read against Fable 5, framed the way the wiki already frames Anthropic’s own lineup:
- Sol vs Fable 5 at the frontier tier: Sol is
$5/$30vs Fable 5’s$10/$50— 50% cheaper input, 40% cheaper output — and OpenAI’s own ExploitBench line claims frontier-competitive cyber output at ~1/3 the tokens. Sticker price alone doesn’t decide it: Fable 5 is token-hungry (500k–1M+ token sessions) and the wiki’s standing guidance is to reserve it for the heavy/long-horizon tail. If Sol holds capability, it pressures exactly that “worth the token cost” calculus. - Terra/Luna reproduce the “route down a tier” pattern OpenAI-side. The wiki’s Fable 5 guidance — “route routine sessions (compiles, inbox-refresh, lint sweeps) back to Opus 4.8, keep Fable 5 for the heavy tail” — has a direct GPT-5.6 analogue: keep Sol for the hard tail, push balanced production to Terra (15, undercutting Fable 5 ~4x on input), and dump high-volume classification/routing on Luna (6). One vendor, three cost rungs, no cross-provider integration cost.^[inferred routing synthesis]
- Safety-classifier routing is the Reddit poster’s actual point. GPT-5.6’s preview safeguards include real-time cyber/biology misuse classifiers that can pause generation for larger-model review, plus account-level abuse review^[secondary: explainx]. That mechanically parallels Fable 5’s topic-gated Opus 4.8 fallback (documented in claude-fable-5-mythos-5): both frontier vendors now interpose a routing/gating layer that can divert or slow a request mid-flight. Budget for the friction (blocks, refusals, latency on legitimate dual-use security work) on either stack.
- Availability caveat that outranks price — now lifted. Sol/Terra/Luna were preview-gated to ~20 US-cleared orgs via API + Codex only^[secondary]. See fable-5-mythos-5-federal-shutdown for the mirror-image export-control story on Anthropic’s side. Update (2026-07-10): that gate is gone — GPT-5.6 reached general availability on 2026-07-09, bundled into the new unified ChatGPT Work app (see below), and independent creators had broad hands-on access within the launch window. GPT-5.6 is now a routable choice alongside Fable 5 / Opus 4.8 / Sonnet 5 / GLM-5.2, not just a price-comparison datapoint.
Benchmarks & Safeguards
- ExploitBench (official): Sol competitive with Mythos Preview at ~1/3 the output tokens; evaluated with the ExploitBench API harness, 5 seeds, reasoning continuity.
- ExploitGym (official, UC Berkeley + OpenAI + other labs): all three tiers show strong cyber gains as reasoning increases.
- Terminal-Bench: “GPT-5.6 Sol Ultra” reportedly posts the top score^[secondary: DataCamp, explainx]. For the live board the wiki already tracks — Codex CLI + GPT-5.5 (83.4%) and Claude Code + Fable 5 (83.1%) tied for the lead at the last capture — see terminal-bench.
- Preparedness Framework^[secondary: Handy AI, single source]: all three rated High for Cybersecurity and High for Biological & Chemical, Below High for AI Self-Improvement. The system card reportedly notes Sol “were unable to carry out autonomous, end-to-end attacks against hardened targets” and shows “a greater tendency than GPT-5.5 to go beyond the user’s intent” in internal coding traffic — an overeager/destructive-action note that rhymes with the Mythos-family self-guards.
- Safeguard stack (preview)^[secondary: explainx]: model-trained cyber refusals; real-time cyber/biology misuse classifiers (can pause for larger-model review); account-level review; 700,000+ A100-equivalent GPU-hours of automated red-teaming for universal jailbreaks; ongoing third-party human red-teaming.
GPT-5.6 jailbreak-resistance investment vs. real-world outcome
Existing claim: (this article, verified 2026-07-03) — Sol’s preview safeguard stack included “700,000+ A100-equivalent GPU-hours of automated red-teaming for universal jailbreaks,” framed as a strong pre-release hardening investment. New source says: (raw/A_Model_Explosion_-_GPT_5.6_Sol_Grok_4.5_and_Meta_Muse_Rewrite_the_Rules.md) — The UK AI Security Institute found a universal jailbreak for GA GPT-5.6 within hours of release, without sacrificing the model’s capabilities. OpenAI has mitigated the specific jailbreaks found, but the Institute “expect[s] further red teaming to surface similar jailbreaks.” An Anthropic researcher publicly said the ease of jailbreaking, combined with high reward-hacking rates in GPT-5.6, left them “pretty worried about the alignment of that model,” adding: “I hope OpenAI didn’t rush this model release just to keep up with Fable.” Status: unresolved — a well-resourced pre-release red-teaming investment and a fast post-release external find are not strictly incompatible, but the practical takeaway of “extensively red-teamed against universal jailbreaks” needs the caveat that a universal jailbreak was still found quickly once outside testers had access. Revisit if OpenAI publishes a fuller account or the UK AISI issues a follow-up.
GA benchmark roundup (2026-07-09 launch week, mostly creator/secondary-sourced)
The ExploitBench/ExploitGym/Preparedness-Framework numbers above remain the only primary-source (openai.com) benchmark data for GPT-5.6. Everything below is creator- or secondary-sourced from GA-week hands-on testing and third-party leaderboards — directional, not verified-primary, until an official system card publishes these figures.
- Agent’s Last Exam: Sol (extra-high reasoning) ~54% vs Fable 5 (max) ~45%^[secondary, creator-cited from the official OpenAI release chart]. Notable pedigree — co-led by UC Berkeley, 55 industries, 300 experts, tasks derived from real completed projects (“No vibes, no human judges, fully reproducible” — Dawn Song). Read with the wiki’s standing caveat: no single benchmark crossing has yet triggered an AI-first switchover the way SWE-bench’s 60%→~100% run didn’t singularly end manual coding.
- Artificial Analysis Coding Index: Sol 80 vs Fable 77, at lower cost^[secondary]. Caveat: this composite draws on Terminal-Bench and “Deep SWE-bench”^[inferred — the source audio transcribes this “Deep Suey”; normalized here, not confirmed against an official benchmark listing] but not two newer, harder benchmarks (FrontierSWE, SWE-Marathon) where Sol’s results aren’t yet published; on SWE-Marathon specifically, Grok 4.5 leads and Fable 5 trails — see the new Grok 4.5 article. The “Sol beats Fable at coding” framing is benchmark-selection-dependent.
- ARC-AGI-3 (abstract-reasoning benchmark, “especially penalizing to models”): Sol 8% vs other tested models below 2%; Fable reportedly not run due to cost^[secondary, single source].
- AutomationBench (Zapier): Sol (max) edges Fable by a 0.7% score margin at roughly the same cost^[secondary] — a much narrower gap than the Agent’s Last Exam or Coding Index deltas above.
- GDPval: Fable holds a slightly higher Elo than Sol, at roughly 3x the cost^[secondary]. Separately, GA-week coverage also has Sol “outperform[ing] everything but Claude Fable” on GDPval, with Fable’s edge described as narrow^[secondary, single source: Matt Wolfe hands-on] — both sources agree Fable leads GDPval by a small margin at a real cost premium.
- Terminal-Bench 2.1 (GA-week figures — a distinct capture from the wiki’s tracked board): Fable 84%, Grok 4.5 83%, GPT-5.6 88% (Soul Ultra 91.9%)^[secondary, single source, creator-cited — treat as a separate data point from the terminal-bench.md-tracked 83.1%/83.4% harness-pairing figures rather than a direct overwrite; different runs/harnesses can legitimately diverge].
- “Deep SWE-bench”^[inferred name — audio transcribed “Deep here” / “Deep Suey,” likely a Deep-SWE-bench variant]: Grok 4.5 62%, Fable 5 66%, GPT-5.6 72.7%^[secondary, single source].
- Buybench: GPT-5.6 tiers sweep the top 4 spots — Soul Pro #1, Terra Pro #2, Terra #3, Soul #4. Soul Pro generated the winning entry for 4 / ~6 minutes for its prior-gen entry — a concrete same-vendor generational cost/speed delta^[secondary, single source: Matt Wolfe hands-on].
- Computer/browser use: Sol “beats out everything, including Mythos and Fable”^[secondary, single source, unspecified benchmark — a qualitative claim pending a named benchmark].
- GPQA (Diamond, graduate-level Q&A): Sol ties Mythos^[secondary, single source].
- Simple Bench (creator’s own private common-sense-reasoning benchmark, cited by The Economist / MIT Tech Review): an unannounced Soul Pro variant surfaced via OpenRouter scores 71.7% — ~10 points below Fable, and not far ahead of Grok 4.5; base Soul scores ~65%^[secondary, single source].
Single-tester head-to-head vs Fable 5 (creator tests, 2026-07-09, n=1 per scenario)
Source: raw/I_Tested_GPT_5.6_Sol_vs_Fable_5._What_You_Need_To_Know..md. One creator ran Fable 5 (Claude Code) against GPT-5.6 Sol (Codex) side-by-side on identical /goal prompts, then 27 stateless one-shot API calls. This is one person’s testing, not a controlled study — confidence medium, not high; read the deltas as directional.
| Test | Fable 5 | Sol | Winner (creator’s subjective call) |
|---|---|---|---|
Open-world bike game (/goal, identical prompt) | 21m37s, ~$14.22, ~90k output tokens | 23m, ~$4.50, ~31k output tokens | Fable (quality) |
“Most impressive interactive website” (/goal) | 23m, $19.24, 80k output tokens | ~7m, ~$1.22, ~20k output tokens | Fable (quality) — Sol ran ~20x cheaper |
5 fundamentally different visual elements (/goal) | 15m, ~$15, 65k output tokens | ~7m, ~$1.22, ~22k output tokens | Sol (creator’s pick — “better diversity”) |
| 27 stateless one-shot API calls | 3 wins, $63 total, 0.966 score-when-answering | 24 wins, $16 total, 0.98 score-when-answering | Sol on raw win count — but near-parity (0.98 vs 0.966) when Fable actually answered; most of Fable’s losses were refusals to answer at all |
Creator’s qualitative verdict: Fable is “a better manager” / co-founder — stronger at creative work, writing, brainstorming, strategic advice, and avoiding over-engineering. Sol is “a really, really good worker” — cheaper, faster, better at computer use, and more willing to play devil’s advocate / hunt bugs. The creator’s positioning: GPT-5.5 ≈ Opus 4.8 < Sol < Fable 5, with “still a pretty large gap” between Sol and Fable — closer in practice to an Opus-4.8-tier model at Opus-4.8-tier pricing than a true Fable-5 rival, despite some benchmarks suggesting near-parity.^[creator’s framing, single source]
A second, independent creator anecdote (Matt Wolfe, GA week) reported a complementary-use pattern rather than a straight substitute: after building most of a website with Fable 5, handing the finished code to GPT-5.6 surfaced security vulnerabilities (including an exposed API key) that Fable had missed^[secondary, single source: raw/AI_News_-_GPT-5.6_and_the_new_Super_App_are_a_Massive_Leap.md].
For the independent counter-read on whether these Mythos-class cyber gains are overhyped, the same lens applies here as to Anthropic: see Epoch AI’s Cyber-ECI analysis (exploit-development jumps are real; vulnerability-discovery gains are easy to overstate).
ChatGPT Work — OpenAI’s Unified Super-App (new, 2026-07-09)
Source: raw/AI_News_-_GPT-5.6_and_the_new_Super_App_are_a_Massive_Leap.md. Alongside the GA launch, OpenAI merged three previously separate surfaces — the Codex app, the ChatGPT app, and the Atlas browser — into a single app. This is a genuinely new OpenAI product-architecture move with no prior wiki coverage.
- One app, two modes. A toggle switches between Work mode (general assistant — tell it what you want and it decides whether to answer directly, connect to a tool, or go build something) and Codex mode (development-focused).
- In-app browser replaces Atlas. The standalone Atlas browser is being folded in; browsing now happens inside the ChatGPT app’s sidebar.
- In-app terminal (Codex mode). The Codex-mode sidebar adds a review pane and a terminal pane alongside the shared browser/files panels.
- One-click site hosting —
chatgpt.site. A new “Sites” flow turns a prompt into a hosted website with no manual database/CDN setup; a “Publish” toggle makes it accessible to “anyone on the internet” at achatgpt.siteURL. - Model slider from Terra Light to Soul Ultra. A simplified mode replaces the tier/effort picker with a single slider — the lowest setting uses 5.6 Terra Light, the highest uses 5.6 Soul Ultra (heaviest credit consumption). 5.5 remains selectable alongside the 5.6 family.
- Personal-assistant framing. Demoed connecting to Gmail, Calendar, Slack, Google Drive, and meeting-notes tools to build a daily priority “control tower” and recurring scheduled digests — positioning Work mode as an OpenAI-side answer to agent-driven personal-assistant workflows.^[creator demo, single source]
- How OpenAI describes it (2026-09-29, Lenny’s Podcast with Tara Seshan, who leads product for Codex and ChatGPT Work at OpenAI). The app now has a ChatGPT/Codex drop-down and a Chat/Work toggle. In Work mode “under the covers this is Codex,” with coding UI such as the work tree hidden; Seshan says Codex users “aren’t missing out on anything by not switching modes.” Work runs in the cloud, so a task started on mobile keeps going: “take like a long subway ride… when you pop out after having no service, the thing is done for you.” Her own habits: “Now I just make sites all the time” instead of documents (Sites have a database and can be public, team-only or private), and
/visualizein Codex (“visualize my ChatGPT usage until now”). The stated goal is that “users do not need to make decisions between picking between all these different options”: one box, no toggle.
Related
- Luna) — the successor family (2026-09-03 and 2026-09-22); current prices and routing.
- grok-4-5-xai — xAI’s SpaceX/Cursor-collaboration model; a third frontier-adjacent competitor datapoint, cheaper than both Sol and Fable 5, and the one that leads SWE-Marathon where Sol has no published results.
- claude-fable-5-mythos-5 — Anthropic’s Mythos-class flagship (50) and the direct frontier-tier comparison anchor; also the source of the topic-gated Opus 4.8 fallback this piece parallels.
- claude-sonnet-5 — Anthropic’s mid-tier (15 std) that ties Terra on output; the “route down a tier” neighbor on the Claude side.
- glm-5-series-zai — open-weight value frontier (~4.40) that undercuts even Luna; the price-floor competitor.
- kimi-k3-moonshot — Moonshot’s 2.8T open-weight model reported neck-and-neck with Sol on DeepSWE; the open-weight challenger at the same frontier tier.
- gemini-cli — Google’s competing frontier-model CLI surface; the third major closed-vendor agentic stack.
- fable-5-mythos-5-federal-shutdown — the mirror-image US-government frontier-model gate on Anthropic; context for GPT-5.6’s ~20-org preview restriction.
- terminal-bench — the agentic benchmark backdrop where GPT-5.x and Claude trade the lead.
- epoch-mythos-cyber-capabilities-overhyped — independent cyber-capability read; the counter-lens for Sol’s ExploitBench claims.
- Hugging Face Sandbox-Escape Incident (July 2026) — Sol, paired with an unreleased more-capable OpenAI model, chained zero-days out of an internal cyber-benchmark sandbox into Hugging Face production. The strongest public datapoint on this family’s offensive capability with refusals disabled.
- _index — competitor-model / benchmark tracking topic index.
Open Questions
- Official benchmark verification. GA week (2026-07-09) produced Terminal-Bench 2.1, “Deep SWE-bench,” Buybench, Agent’s Last Exam, Artificial Analysis Coding Index, and ARC-AGI-3 figures (see GA benchmark roundup above) — but all are creator- or secondary-sourced from launch-week hands-on testing, not an official OpenAI system card. Verify against the GPT-5.6 system card when OpenAI publishes one.
- Context window. Sol’s 1.5M-token window (up ~43% from GPT-5.5 Pro’s 1.05M) is single-secondary-sourced (Handy AI) — confirm on the official model page. Terra/Luna context not stated.
Long-context pricing tier. GPT-5.5 bumped input rate past ~272K tokens; GPT-5.6 lists a single flat rate per model — whether a long-context surcharge applies at GA is unknown^[secondary: eesel].Answered (2026-09-29, Epoch Brief of 2026-09-12; the full Epoch report was not fetched): GPT-5.6 models do increase in price past 272k input tokens, while Claude 5 prices stay fixed. Epoch researcher Jason Li measured time-to-first-token as context grows to 1M tokens: GPT-5.6 shows a noticeable quadratic component, Claude 5 stays close to linear, which Epoch reads as evidence of different underlying architectures. Practical read: for 272k+ contexts, both cost and latency favour Claude 5-class models.- UK AISI universal-jailbreak follow-up. The Institute “expect[s] further red teaming to surface similar jailbreaks” beyond the ones OpenAI already mitigated (see contradiction callout in Benchmarks & Safeguards) — no follow-up report ingested yet.