September 2026 archive
Every AI model release in September 2026
- 2026-09-30Release
Google announces Gemini 4 Argon — frontier model, not yet generally available, and priced at $2/$10 only for an introductory period
Official source →Google announced Gemini 4 Argon on 2026-09-30 (20:00 UTC) and two days later, checked 2026-10-02, it is still not generally available: no API model identifier appears in Google's own model list, no general-release date is given, and the model is rolling out first to trusted cyber defenders under the Fairwind Program. The $2/$10 introductory rate doubles to $4/$20 after the intro period, and no vendor-stated context window, knowledge cutoff or reasoning-effort control is published.
Two labs have measured it. Artificial Analysis puts it at 57.1 on Humanity's Last Exam without tools, 9.3 points above Gemini 3.8 Flash at that same tier against a 2-point band, though on Humanity's Last Exam this site records five other models below max effort — Gemini 3.7 Flash and 3.8 Flash and Grok 4.6 at high, Muse Spark 1.2 and Grok 4.7 at xhigh — so its position in that column describes the column, not a matched ranking; vals.ai ranks it fifth on Terminal-Bench 4.0 at 57.58% and first on its own Vals Index at 68.90%.
Its page is live; what is still unstated by Google is recorded there and below.
- 2026-09-29Release
InclusionAI (Ant Group) ships Ling 3.1 Flash — 560B/25B hybrid reasoning, free on two gateways through October 13
Official source →Recorded 2026-10-11, twelve days after the fact: this is a dated snapshot of a release that happened while this site was not watching the gateway layer, not a same-day report. InclusionAI — Ant Group's model lab, so an attributed release rather than a stealth listing like Ox Alpha or Fledge Alpha — shipped Ling 3.1 Flash on 2026-09-29. It is a hybrid-reasoning model with 560B total and 25B active parameters per token, text-only input and output, and tool calling. The route serves a 262,144-token context window against a vendor-stated 1M-token design target; InclusionAI says it will enable the larger window and publish open weights after the free trial ends, and neither is verifiable from outside yet.
Access, not capability, is the story. It is free through 2026-10-13 on Vercel AI Gateway, where the `inclusionai/ling-3.1-flash-free` id stops serving when the promotion ends while the standard id begins billing, and it is also listed free on OpenCode Zen. It is the second entry in that run whose maker is named, after Meituan's LongCat 2.5 Preview on 2026-09-25, which is also free on OpenCode Zen; the rest arrived unattributed. A free route is not a measured one. No board this site tracks has scored it: Artificial Analysis has no page for the model, and vals.ai, Toolathlon and LiveBench each return nothing when searched directly on 2026-10-11. The only benchmark figures that exist are eight values on Ant Ling launch screenshots captured 2026-09-30, with no harness, grading setting or effort tier documented, so this site records no score from them.
The context claim is the part worth watching, because it is exactly the shape this site exists to discipline: 262,144 tokens served today, 1M claimed as the design target, and a promise to close the gap later. A spec-sheet number the current route does not serve is not a context window. Marked minor rather than major: the maker is known, the price is zero, and the only verifiable facts are the architecture and the routes.
- 2026-09-29Release
OpenAI ships GPT-6.1 Sol — same $2/$10 as GPT-6 Sol, one real independent gain, ties Astra on HLE
Official source →$2/$10 per million tokens unchanged; cached input halves to $0.10. OpenAI pitches it as near-Astra at a fifth of Astra's price.
3 of 12 tracked benchmarks carry an independent score one day after launch. Against GPT-6 Sol at max effort, Artificial Analysis's Humanity's Last Exam shows a real gain (52.9% vs 47.9%, band 2); LiveBench (81.6 vs 79.3) and AA's Codex-agent DeepSWE run (69.6% vs 69.0%) are ties.
Against GPT-6 Astra at max effort, AA's HLE (54.7%), LiveBench (82.2) and AA's DeepSWE run (67.6%) all read as ties.
GPT-6 Sol's model page points to "the newer Sol model" but carries no deprecation notice.
- 2026-09-28Release
Claude Sonnet 5.5 launches — Sonnet 5's $2/$10 unchanged, "not at the capability frontier" by Anthropic's own card
Official source →Priced $2/$10 per million tokens, unchanged from Sonnet 5 including cache and batch rates, flat across the 1M window; Anthropic claims 30%+ faster output and up to 30% lower cost per task than Sonnet 5 — its own tests — and its system card says the model "is not at the capability frontier."
One day post-launch, 3 of the 12 benchmarks this site tracks carry an independent score. Two same-tier comparisons with Sonnet 5: Humanity's Last Exam is a real gap, 55.0 vs 41.3 (Artificial Analysis, max effort); LiveBench at xHigh is a tie, 77.8 vs 76.0, with Agentic Coding well below Sonnet 5's (39.3 vs 59.4).
Sonnet 5's page now carries a "Legacy" badge while the deprecations page lists it "Active" — the same disagreement as Opus 5 — and Sonnet 5 is the visible fallback for Sonnet 5.5's cyber and frontier-LLM safety blocks, so a published 5.5 score can contain Sonnet 5 answers.
- 2026-09-25Release
Meituan releases LongCat-2.5-Preview — 1.6T parameters, 1M context, no benchmarks published
Official source →Meituan's announcement lists 1.6T parameters (~48B active), a 1M-token context, native multimodal input and a focus on long-running agents. The API price, $0.30 input / $1.20 output per million tokens, is labelled a limited-time discount.
Meituan published no benchmark numbers, no independent board lists the model as of 2026-09-27, and no weights have been released or announced as of 2026-09-27, unlike LongCat 2.0. With nothing measurable yet, no model page is added.
- 2026-09-23Release
Anonymous "Space Bunny Alpha" appears on OpenRouter — free, 1M-token context, maker undisclosed
Official source →OpenRouter lists Space Bunny Alpha from September 23 (14:48 UTC, per its public models API) with a 1M-token context window, up to 524,288 output tokens, text, image and video input, and $0 per million tokens through its public API. The listing credits only an anonymous provider, marks reasoning as mandatory across five effort tiers (default max), and carries an expiration date of 2026-10-05. OpenCode Go also lists a "Space Bunny Free" option, free for a limited time.
As of 2026-10-01, no standard leaderboard carries it: LiveBench, ARC-AGI-2, DeepSWE, the official Terminal-Bench 2.1 board and Artificial Analysis (models list and changelog through 30 September) all show no row.
Two outside sources do publish figures, and their provenance is not the same. AI Benchy, an independent public leaderboard, scores it 7.5 at #118 on a run tested 2026-09-30 — that number is taken from AI Benchy itself.
An unaffiliated third-party site publishes its own runs of GPQA Diamond (82.0%, 60-question subset), MMLU-Pro (75%, sample not disclosed) and HLE (46.1%, 300-question subset, 95% CI 40.4-51.8, seven unscored questions), plus a token-efficiency claim. Each is reproduced below with its caveats; none is adopted as a score.
No model page is added.
- 2026-09-22Release
GPT-6 Luna launches alongside Sol — cheapest GPT-6 at $0.10/$0.50, ties GPT-5.6 Luna on every clean comparison
Official source →Same tiered pricing rule as Sol at one-twentieth Sol's price — and half GPT-5.6 Luna's input rate, 42% of its output rate ($0.20/$1.20, a rate OpenAI itself calls promotional).
3 of 11 tracked benchmarks carry an independent score, and all three tie GPT-5.6 Luna inside the noise band, numerically slightly lower each time: Humanity's Last Exam 38.5% vs 39.5%, LiveBench 72.0 vs 73.6, ARC-AGI-2 59.31% vs 59.6%, same evaluators, max effort.
GPT-5.6 Luna is not deprecated; OpenAI's deprecations page lists it as the recommended replacement for two other retiring models.
- 2026-09-22Release
OpenAI launches GPT-6 Sol — half GPT-5.6 Sol's promotional price, no measurable gain over it yet
Official source →$2/$10 per million tokens up to 272K prompt tokens (2x input/cache, 1.5x output above it). OpenAI's table reads "50% cheaper" than GPT-5.6 Sol, but calls GPT-5.6 Sol's $4/$20 rate itself "promotional."
3 of 11 tracked benchmarks carry an independent score, and on the two clean matched comparisons GPT-6 Sol ties its predecessor, numerically slightly lower: Humanity's Last Exam 47.9% vs 49.49% and LiveBench 79.3 vs 81.0, same evaluators, max effort, both inside the noise band.
AA's own Codex-agent DeepSWE run (69.0%, close to OpenAI's self-reported 68.8%) uses a different harness from GPT-5.6 Sol's board score.
GPT-5.6 Sol carries no deprecation notice.
- 2026-09-22Release
Claude Opus 5.5 launches — Anthropic's "new leading model" at 20% below Opus 5's per-token price
Official source →Priced $4/$20 per million tokens, 20% below Opus 5's $5/$25 per token, flat across the full 1M-token window; Anthropic separately claims 40% lower cost than Opus 5 on typical workloads, its own test.
Anthropic calls it "the new leading model," performing "at the level of Claude Fable 5.1 on most work" at 40% of Fable 5.1's price.
One day post-launch, 2 of the 11 benchmarks this site tracks carry an independent score, and both back that up: Humanity's Last Exam (61.4%, Artificial Analysis, max effort — the highest AA has recorded, 2.3 points past Fable 5.1, just outside the noise band) and LiveBench (83.2, tied with Fable 5.1's 83.4).
Opus 5's own page now carries a "Legacy" badge, but Anthropic's model-deprecations page still lists it "Active" — two official sources disagree.
- 2026-09-22Release
Xiaomi launches MiMo-V2.6-Flash — 309B open-weight at $0.14/$0.28 per 1M tokens
Official source →MIT-licensed 309B / 15B sibling at flat $0.14/$0.28. Zero independent measurements at launch: no Artificial Analysis page (404 checked 2026-09-22), no listing on the seven boards checked live, all four tracked scores Xiaomi's own; same DeepSWE source split as Pro (67.9 on the card vs 65.7 as this RL run's after-training endpoint in the announcement).
- 2026-09-22Release
Xiaomi launches MiMo-V2.6-Pro — MIT-licensed 1.02T open-weight at $0.435/$0.87 per 1M tokens
Official source →Open-weight flagship under MIT: 1.02T total / 42B activated, 1M context, flat $0.435/$0.87. Artificial Analysis independently indexes it at 46, and its Humanity's Last Exam chart lists the model at 49.35 — the one independent score this site tracks for it (corrected 2026-09-23; this entry first said AA published no per-benchmark scores).
The seven boards checked live on launch day (tbench.ai, deepswe.datacurve.ai, toolathlon.xyz, snorkel.ai, livebench.ai, arcprize.org, matharena.ai) do not list it, so the four coding and agent numbers are Xiaomi's own.
Xiaomi's two official sources also disagree on DeepSWE v1.1 — 71.9 on the model card vs 72.6 as this RL run's after-training endpoint in the announcement's own training write-up; recorded unresolved.
- 2026-09-21Release
Grok 4.7 launches — same price as Grok 4.6, thinner independent record so far
Official source →Priced and speed-matched to Grok 4.6, per xAI's own launch post.
Two days post-launch, only 2 of the 8 benchmarks where Grok 4.6 has an independent score carry one for Grok 4.7 — Humanity's Last Exam (43.1%, Artificial Analysis, xhigh) and LiveBench (77.4 overall, xHigh, on the same release Grok 4.6 sits on) — and both read close to Grok 4.6 (42.9% and 78.0 respectively), though the HLE comparison isn't same-tier (Grok 4.6's tracked score used high effort, not xhigh). Grok 4.6 itself did not reach its full 8-benchmark independent record until 5-12 days post-launch, so this is not a like-for-like launch-day comparison either way.
xAI's own model card claims 71.0% on DeepSWE, but deepswe.datacurve.ai still shows no Grok 4.7 row, so that figure is unverified; GPQA Diamond, SWE-bench Verified, LiveCodeBench, ARC-AGI-2 and Terminal-Bench 2.1 have no score at all yet.
xAI does not call this a replacement for Grok 4.6, which stays listed unchanged on the same pricing page.
Parameter count is undisclosed by xAI; a widely circulated third-party 2.1T figure traces to no xAI source and is not used here.
- 2026-09-20Release
StepFun launches Step 5 Preview — $1.00/$2.70 per 1M tokens, one independent score, open weights promised for October 15
Official source →StepFun pitches frontier-level software-engineering performance at a flat $1.00/$2.70 per million tokens. Only one of the six scores this site tracks for it is independent — Humanity's Last Exam without tools, 46.48, run by Artificial Analysis — while the coding and agent numbers (DeepSWE 67.7, Terminal-Bench 2.1 85.0, Toolathlon-Verified 74.1) are StepFun's own and none of the boards behind those benchmarks lists the model yet.
The open weights are a plan for October 15, not a release: the model is hosted-only, and the third-party copies posted on Hugging Face are not a StepFun release.
- 2026-09-17Release
Union Alpha revealed as Unbiased's Pareto 26.9 — a multi-model blend, now paid at $2.50/$7.50 per 1M tokens
Official source →OpenRouter's own stealth page now says the listing was "revealed to be Pareto by Unbiased" and that the free stealth period has ended. Unbiased describes Pareto as a blend that calls multiple LLMs in parallel on every request and synthesizes the results — explicitly not a router — but names none of the models inside it, so this site cannot attribute a score to a single lab, weights file or checkpoint.
Its model card publishes five numbers (DeepSWE 74, Terminal-Bench 4.0 51, MMMU-Pro 78, HLE without tools 49, ArXivMath 88) that are Unbiased's own; its how-it-works page points to a public evaluation harness, but none of the numbers has been run independently, and none is added here.
- 2026-09-16Release
Anonymous "Union Alpha" appears on OpenRouter — free public API, maker undisclosed
Official source →Update, 2026-09-17: revealed as Unbiased’s Pareto 26.9 — see the September 17 entry. What follows is the launch-day record.
OpenRouter lists Union Alpha from September 16 with a 262K context window and $0 per million input and output tokens, available through its public API. The listing describes a multimodal model for research, coding and agentic work, but credits only an anonymous third-party provider. OpenCode Go also lists it as free for a limited time.
Access is verifiable; model identity and benchmark performance are separate questions. No model page or scores are added on the strength of this listing.
- 2026-09-10Release
DeepSeek V4.1 Flash launches — replaces V4 Flash; V4 Pro API remains available
Official source →Status corrected 2026-09-17 against DeepSeek's September 10 changelog: V4 Flash and V4 Flash Vision Exp are retired, with their API names temporarily routed to V4.1 Flash. V4 Pro service continues after September 14 with billing unchanged; the prior claim here that all Pro requests would redirect on that date is withdrawn. V4 Flash remains a previous version here; no newer model sits in the DeepSeek V4 Pro tier, so V4 Pro is current.
Pricing drops to $0.15/$0.60 off-peak (from V4 Flash's $0.22/$0.66, V4 Pro's $0.66/$1.98), and the architecture changes substantially — a new Causal Encoder-Decoder design DeepSeek says cuts KV-cache size roughly 4x versus V4 Flash, plus native multimodal input.
The performance claims lack independent confirmation at the launch check: as of this release, vals.ai, tbench.ai, Artificial Analysis, deepswe.datacurve.ai, toolathlon.xyz, arcprize.org, livebench.ai and matharena.ai all checked live and none list this model yet — every score on its page is DeepSeek's own number.
- 2026-09-09Price change
GLM-5.3-Flash launch promo ends — back to $0.15/$0.50 per 1M tokens
Official source →The 50% launch discount ($0.075 / $0.25) expired on schedule at 24:00 UTC+8, exactly as Z.ai's pricing page had stated from day one; the $0.15 / $0.50 list rate is now the live price, confirmed against OpenRouter's price feed on 2026-09-22. Nothing about the model changed — only the price.
- 2026-09-04Release
Anonymous "Omen Alpha" appeared on OpenCode Go — no longer listed as of September 17
Official source →Omen Alpha was announced on 2026-09-04 as exclusive to OpenCode Go subscribers, without a named maker or model card. Update checked 2026-09-17: OpenCode's Go documentation no longer lists Omen Alpha; it now lists Union Alpha, also available through a public OpenRouter API. Neither listing establishes that Union Alpha is a renamed Omen Alpha. The earlier claim here that outsiders could not benchmark Omen Alpha was too strong: a third-party llmbench run was already documented, although it was not a result from a benchmark tracked by this site.
- 2026-09-03Release
GPT-6 Astra launches — OpenAI's first model to cross its own "Critical" cybersecurity threshold
Official source →Five of the eleven benchmarks this site tracks carry an independent score so far, but only Humanity's Last Exam clears a clean same-tier, same-harness comparison against GPT-5.6 Sol (+5.2 points) — the rest are ties, harness mismatches, or the saturated GPQA Diamond board. Does not replace Sol, Terra, or Luna: OpenAI's own materials never call it a successor, and all three remain sold unchanged.
- 2026-09-02Release
Muse Spark 1.3 launches — same price as 1.2, weights decision now explicitly undecided
Official source →Pricing carries over unchanged from Muse Spark 1.2 ($1.25/$4.25 standard, $0.10/$0.20 Contributor tier).
Four of the eleven benchmarks this site tracks already carry an independent score one day after launch, all Artificial Analysis at its 'max' tier except LiveBench: GPQA Diamond (93.8%), Humanity's Last Exam (49.1%), Terminal-Bench 2.1 (85.8%), and LiveBench (81.6).
Where the comparison against Muse Spark 1.2 is clean, the gain is real: LiveBench gains 3.6 points at a matched reasoning-effort tier, clearing that benchmark's own noise band. HLE's headline +3.6 points mixes tiers the same way GPQA Diamond's does, though — on a matched xhigh-to-xhigh basis the real gain is only about 2.0 points (Terminal-Bench 2.1's +5.6 is a tie; GPQA Diamond is saturated and moot either way).
DeepSWE, ARC-AGI-2, LiveCodeBench, SWE-bench Verified, Toolathlon-Verified, Agents' Last Exam, and HMMT Feb 2026 have no Muse Spark 1.3 score yet; Meta's own self-reported 75.4% DeepSWE claim has no independent figure to check it against.
Reporting describes Meta as having explicitly not decided whether to open the weights, citing EU AI Act Article 53's systemic-risk carve-out — a more uncertain framing than 1.2's own still-unfulfilled 'open weights coming soon' promise.
(Update 2026-09-29: this site now tracks twelve benchmarks, and Artificial Analysis has since revised the three max-tier figures to 93.5, 48.7 and 84.3, which trims HLE's headline gain to +3.2 and Terminal-Bench 2.1's to +4.1 — neither verdict changes.)
- 2026-09-02Release
Gemini 3.8 Flash launches — same price as 3.7 Flash, built on its checkpoint, not a new pretraining run
Official source →Google's own model card states plainly "Gemini 3.8 Flash is based on Gemini 3.7 Flash" — pricing is identical at $0.75/$3.75 per MTok (introductory through 2026-12-31), and the knowledge cutoff carries over unchanged at March 2026. A restricted sibling, Gemini 3.8 Flash Cyber, ships the same day for vulnerability detection under Google's invitation-only Fairwind Program.
Six of the eleven benchmarks this site tracks already carry an independent score one day after launch — GPQA Diamond (94.44%, vals.ai), LiveCodeBench (89.48%, vals.ai), SWE-bench Verified (80.00%, vals.ai), Terminal-Bench 2.1 (87.6%, Artificial Analysis), Humanity's Last Exam (47.8%, Artificial Analysis), and DeepSWE (74% at high effort, tying Claude Opus 5 for the board's top spot) — none from Google's own claimed numbers.
- 2026-09-01Release
Claude Fable 5.1 launches — successor to Fable 5, same price, cheaper cache reads
Official source →Anthropic's own comparison table calls it "Successor to Claude Fable 5" — headline pricing unchanged at $10/$50 per MTok, but cached-read pricing cuts 75% (source: platform.claude.com/docs/en/models/fable-5-1/whats-new-fable-5-1).
All six benchmark scores logged here so far are independently sourced, but Terminal-Bench 2.1 alone splits three ways: 91.4% (Artificial Analysis), 85.02%/79.03%-with-fallback-correction (vals.ai's own harness), and no score at all yet from the benchmark's own board, tbench.ai. The refusal-to-fallback mechanism that put substituted answers into some published Fable 5 scores is still present in Fable 5.1, per vals.ai's own disclosure.