Claude Fable 5.1 is the strongest alternative to GPT-6 Astra — it matches it on coding (100/100) at $10/1M input (GPT-6 Astra costs $10/1M). Claude Opus 4.8 is the budget swap: $5/1M input is 50% cheaper. Kimi K3 is the top open-weight option if you want a model you can self-host.
Last verified Sep 4, 2026/Model data modified Sep 4, 2026
Rankings refresh dailyScored on 6 criteriaNo paid rankings
AnthropicPremium
Input cost
$10.00/1M
Context
1M tokens
Speed
Deliberate
Clear recommendation block
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
GPT-6 Astra is the better pick when response speed matters more than maximum reasoning depth.
OpenAIPremium
Best for
Computer and browser use, long-horizon agentic coding, and frontier math and science work
Price
$10.00/1M
Context
1.1M tokens
Why this page recommends it
Claude Fable 5.1 matches GPT-6 Astra on coding (100/100) at $10/1M input tokens.
Claude Opus 4.8 cuts input cost by 50% ($5 vs $10/1M) while scoring 100/100 on coding.
Kimi K3 is open-weight — self-host it or run it via low-cost API providers at $3/1M input.
Decision notes
Choose Claude Fable 5.1 when you want the closest overall replacement — it targets frontier agentic coding, long-horizon autonomous work, and agentic scientific research.
Choose Claude Opus 4.8 when token volume matters more than peak quality — it is 50% cheaper on input.
Staying with OpenAI? GPT-5.6 Sol is the strongest in-house switch at $2/1M input.
Interactive decision lab
Test the recommendation against your priority
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
#1GPT-6 Astra91 pts
#2Claude Fable 5.191 pts
#3Claude Fable 591 pts
#4Claude Opus 4.890 pts
#5GPT-5.6 Sol89 pts
Quality first
GPT-6 Astra
OpenAI / Premium / Sep 4, 2026
91
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You are cost-sensitive or latency-bound — GPT-5.6 Sol is a fifth of the price — or you need it today in an Enterprise workspace, where it is off by default, or for offensive-security work, which it refuses outside OpenAI Daybreak.
Recommended comparisons
The fastest way to see where the recommendation shifts when your priority changes.
Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.
The case for each model
What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.
Anthropic's September 1, 2026 frontier release and the new capability ceiling for coding, agents, and scientific work. Base pricing is unchanged at $10/$50, but cache reads dropped 75% to $0.25/1M — roughly 25% cheaper on typical workloads and up to 45% cheaper on agentic ones. 1M context, 128K output, adaptive thinking always on.
Input
$10.00/1M
Output
$50.00/1M
Context
1M tokens
Speed
Deliberate
What people actually use it for
Agentic scientific research — 52.6% on Terminal-Bench-Science 0.1, more than double Fable 5's 24.7%
Long-running autonomous coding agents that plan, run, and debug across a whole repository
Cache-heavy agent loops where the 75% cache-read cut ($1.00 → $0.25 per 1M) is the real saving
Where it wins
52.6% Terminal-Bench-Science 0.1 — 2.1x Fable 5 (24.7%), well clear of Opus 5 (29.0%) and GPT-5.6 Sol (22.4%)
55.8% Terminal-Bench 4.0 agentic coding, ahead of Opus 5 (52.3%) and Fable 5 (42.0%)
Cache reads cut 75% to $0.25/1M — ~25% cheaper for typical use, ~45% for heavily agentic work
Independent Vals AI evaluation ranks it #1 of 51 on the Vals Index, #1 on LiveCodeBench (90.5%) and MMLU Pro (92.4%)
1M-token context and 128K max output at standard rates, with adaptive thinking always enabled
Where it falls down
Base rates are still $10/$50 per 1M — double Claude Opus 5 for anything that is not cache-heavy
Anthropic published no SWE-bench Verified or SWE-bench Pro figure for 5.1 at launch
On Claude Pro it only runs on pay-as-you-go credits; Max includes it up to 50% of weekly limits
Deliberate, high-latency profile — the wrong choice for interactive, latency-bound apps
Skip it if
You need low latency, or your workload is uncached and cost-sensitive — Claude Opus 5 is half the base price and within a few points on agentic coding.
Our verdict
The new frontier leader, and the rare upgrade that costs less than the model it replaces. Base $10/$50 pricing did not move, but a 75% cut to cache reads makes typical workloads ~25% cheaper than Fable 5 and heavily agentic ones ~45% cheaper — while more than doubling Fable 5 on agentic science and beating Opus 5 on agentic coding. If you were already on Fable 5, switching is a straight win. If you were on Opus 5 for the price, it still costs 2x on uncached tokens.
Released September 1, 2026 alongside Claude Mythos 5.1, the first update to the Mythos-class line since Fable 5 on June 9. API ID claude-fable-5-1; generally available on the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry. Published launch numbers (Fable 5.1 / Fable 5 / Opus 5 / GPT-5.6 Sol): Terminal-Bench-Science 0.1 52.6 / 24.7 / 29.0 / 22.4; Terminal-Bench 4.0 55.8 / 42.0 / 52.3 / 37.3; CursorBench 3.2.0 73.4 / 70.5 / 70.0 / 67.2; AutomationBench 31.4 / 17.1 / 26.9 / 19.6; OSWorld 2.0 strict 41.7 / 36.1 / 39.6; Humanity's Last Exam (no tools) 60.9 / 57.8 / 56.6; GDPval-AA v2 1853 / 1723 / 1824 / 1711. GDPval-AA v2 is rescaled from the v1 numbers quoted on the Fable 5 page and is not directly comparable to them.
OpenAI's September 3, 2026 frontier release — the first GPT-6 model and OpenAI's answer to Claude Fable 5.1 two days earlier. State of the art on computer use (OSWorld 2.0 72.6% in ~47% less time than GPT-5.6 Sol), agentic coding (Terminal-Bench 4.0 57.9%), and frontier math (FrontierMath Tier 4 97.6%). $10/$50 per 1M tokens, 1.05M context, 128K output, knowledge cutoff April 30, 2026.
Input
$10.00/1M
Output
$50.00/1M
Context
1.1M tokens
Speed
Deliberate
What people actually use it for
Computer-use agents that fill forms, update CRMs, run QA in a browser — 72.6% on OSWorld 2.0 at ~40 minutes per task vs Sol's 75
Agentic coding in Codex with cross-context notes — 57.9% Terminal-Bench 4.0, ahead of Claude Fable 5.1 (55.8%)
Frontier math and science — 97.6% FrontierMath Tier 4 and 64.6% Terminal-Bench Science, both well clear of every rival OpenAI tested
Where it wins
OSWorld 2.0 72.6% vs 65.7% for GPT-5.6 Sol, in roughly 47% less time per task — the new computer-use ceiling
Terminal-Bench 4.0 57.9% — ahead of Claude Fable 5.1 (55.8%), Opus 5 (52.3%) and GPT-5.6 Sol (37.3%)
FrontierMath Tier 4 (v2) 97.6% vs Fable 5.1's 87.8%; Terminal-Bench Science 64.6% vs 52.6%; GPQA Diamond 96.0%
1.05M context with 96.3% on OpenAI MRCR 8-needle at 512K–1M (Sol: 73.8%) and 128K max output
OpenAI's lowest misaligned-outcome rates to date: 2.4% on its computer-use safety benchmark vs 22.0% for Sol, 0% scope-creep on impossible cyber tasks vs 48%
Where it falls down
$10/$50 per 1M — five times GPT-5.6 Sol's $2/$10 and the same premium as Claude Fable 5.1; Fast mode doubles it again
Trails Claude Fable 5.1 on Humanity's Last Exam with tools (57.2% vs 65.0%) and on the Artificial Analysis Intelligence Index (61.2 vs 65.7)
OpenAI published no SWE-bench Verified or SWE-bench Pro figure at launch, so it does not appear on our SWE-bench leaderboard
Rolling out over days, not instantly: Enterprise access is off by default, advanced cyber tasks are refused outside OpenAI Daybreak, and the safety layer can pause or stop legitimate agent runs
OpenAI's own system card finds its written reasoning harder to monitor than Sol's
Skip it if
You are cost-sensitive or latency-bound — GPT-5.6 Sol is a fifth of the price — or you need it today in an Enterprise workspace, where it is off by default, or for offensive-security work, which it refuses outside OpenAI Daybreak.
Our verdict
The new computer-use and agentic-coding ceiling, and OpenAI's first model priced like a Mythos-class Claude. Astra beats Claude Fable 5.1 on Terminal-Bench 4.0 (57.9% vs 55.8%), Terminal-Bench Science (64.6% vs 52.6%) and FrontierMath Tier 4 (97.6% vs 87.8%), and it is the only model with a credible OSWorld 2.0 result above 70%. It loses to Fable 5.1 on Humanity's Last Exam and on Artificial Analysis's index, costs five times GPT-5.6 Sol, and ships without a SWE-bench number. If your work is computer use, browser agents or math, it is the pick; for everyday coding at scale, Sol at $2/$10 remains the value default.
Released September 3, 2026. API ID gpt-6-astra; rolling out over the coming days to ChatGPT Plus, Pro, Business and Enterprise (usage inside existing allowances; GPT-6 Astra Pro for Pro/Business/Enterprise; Enterprise off by default), the OpenAI API, Microsoft Azure and Amazon Bedrock. Standard API pricing $10/$50 per 1M tokens; Fast mode is up to 2x speed at 2x price; cache reads and writes have separate rates. Model docs list 1,050,000 context, 128,000 max output, knowledge cutoff April 30, 2026, reasoning efforts up to 'max'. Published launch numbers (Astra / GPT-5.6 Sol / Fable 5.1 / Opus 5): OSWorld 2.0 72.6 / 65.7 / — / 70.2; Terminal-Bench 4.0 57.9 / 37.3 / 55.8 / 52.3; Terminal-Bench Science 0.1 64.6 / 22.4 / 52.6 / 30.0; FrontierMath Tier 4 v2 97.6 / 83.0 / 87.8 / 73.2; GPQA Diamond 96.0 / 94.6 / 93.7 / 93.7; Humanity's Last Exam w/ tools 57.2 / — / 65.0 / 63.6; AutomationBench 41.4 / 18.1 / 31.4 / 26.9; DeepSWE v1.1 74.1 / 72.7 / 67.4 / 73.7; ARC-AGI-2 95.0 / 92.5 / 90.0 / 90.4; ARC-AGI-3 99.9 (OpenAI responses-API harness; ARC Prize's stateless runs score far lower) / 7.8 / — / 30.2; ExploitBench 100.0 / 78.5 / — / 70; SRE-Bench 88.0 / 55.9; Artificial Analysis Intelligence Index v4.1.1 61.2 / 60.9 / 65.7 / 63.1. Meets the Critical threshold for cybersecurity under OpenAI's Preparedness Framework; advanced cyber workflows gated behind OpenAI Daybreak. All figures from OpenAI's launch post and model docs, verified September 4, 2026.
Anthropic's newest Opus flagship — 69.2% SWE-Bench Pro, 88.6% SWE-Bench Verified, 1890 Arena Elo (121 pts ahead of GPT-5.5), and native parallel subagents. Same $5/$25 price as Opus 4.7.
Input
$5.00/1M
Output
$25.00/1M
Context
1M tokens
Speed
Deliberate
What people actually use it for
Running parallel subagent workflows that split, solve, and merge complex engineering tasks
Autonomous PR review and multi-file refactors where accuracy matters more than speed
Deep research synthesis across 1M-token corpora — patents, codebases, legal documents
Where it wins
69.2% SWE-Bench Pro — new #1, up from Opus 4.7's 64.3%
88.6% SWE-Bench Verified and 83.4% OSWorld computer use
Native parallel subagents: orchestrated multi-agent execution in a single call
1890 Arena Elo, 121 points ahead of GPT-5.5
Where it falls down
Deliberate pace — not the right pick for latency-sensitive applications
Same price tier as Opus 4.7; not a budget option
Skip it if
You need low-latency responses, image generation, or a workflow locked to OpenAI tooling.
Our verdict
The best value at the premium tier now that Claude Fable 5 leads on raw capability. 69.2% SWE-Bench Pro, 1890 Elo, and built-in parallel subagents at $5/$25 — half the price of Fable 5. The smart default for serious coding when you don't need the absolute frontier.
Launched May 27, 2026. Available on Claude API, AWS Bedrock, Google Vertex AI, Microsoft Foundry, and GitHub Copilot. Fast mode available at $10/$50 per 1M tokens.
Moonshot's 2.8-trillion-parameter multimodal reasoning flagship with always-on thinking — the largest open-weight model ever released and the closest Chinese challenger to the Western frontier.
Input
$3.00/1M
Output
$15.00/1M
Context
1M tokens
Speed
Deliberate
What people actually use it for
Hardest reasoning tasks — #4 of all models on AA Intelligence Index v4.1 (57.1), ahead of Claude Opus 4.8
Agentic coding at 81.2 FrontierSWE and 88.3 Terminal-Bench 2.0 (Moonshot-reported)
1M-context research synthesis with always-on extended thinking
Where it wins
AA Intelligence Index v4.1: 57.1 — #4 overall, behind only Claude Fable 5 and GPT-5.6 Sol, ahead of Claude Opus 4.8
Open weights (July 26, 2026) — at 2.8T parameters, the largest open-weight release in history
Where it falls down
Most expensive Chinese-lab model ever ($3/$15) with always-on thinking driving high output-token burn and slow responses
2.8T size makes self-hosting impractical despite open weights; consumer signups were paused July 19 over GPU capacity
Skip it if
You need fast responses or predictable output costs — always-on thinking burns tokens.
Our verdict
The first Chinese model to genuinely crowd the Western frontier — #4 on aggregate intelligence ahead of Opus 4.8. The always-on thinking makes it slow and output-heavy, so cost per task runs above the sticker price. A serious Opus-class alternative if latency isn't critical.
Released July 16, 2026; open weights July 26. Cache-hit input $0.30/1M. Subscriptions: Adagio (free) to Vivace $199/mo; full 1M context only on Allegro ($99) and up. New signups paused July 19 near GPU capacity, reopening in batches.
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FAQ
What is the best alternative to GPT-6 Astra?
Claude Fable 5.1 is the strongest overall alternative. It scores 100/100 on coding (GPT-6 Astra: 100/100) and costs $10/1M input vs $10/1M. New frontier leader — better than Fable 5 on every published benchmark, and cheaper to run.
What is the cheapest good alternative to GPT-6 Astra?
Claude Opus 4.8 at $5/1M input — 50% cheaper than GPT-6 Astra's $10/1M. It scores 100/100 on coding, so expect a quality step down on the hardest tasks.
Is there an open-source alternative to GPT-6 Astra?
Yes — Kimi K3 is the strongest open-weight replacement for GPT-6 Astra, scoring 96/100 on coding against GPT-6 Astra's 100/100. You can self-host it or run it through hosted APIs at $3/1M input (GPT-6 Astra costs $10/1M), with no per-seat subscription. Self-hosting trades the licence saving for infrastructure you have to run, so it pays off at sustained volume rather than for occasional use.
What is the best OpenAI alternative to GPT-6 Astra?
GPT-5.6 Sol — same provider, same API surface, $2/1M input vs $10/1M. Best OpenAI flagship — leads terminal coding and agentic browsing.
Is GPT-6 Astra still worth using in 2026?
The new computer-use and agentic-coding ceiling, and OpenAI's first model priced like a Mythos-class Claude.