Announced August 3, 2026 on Alibaba Cloud Model Studio; open weights promised a week after launch. $2/$6 is first-party Model Studio pricing; cache reads from $0.17/1M. Announcement moved Alibaba stock +7% in Hong Kong.
SWE-bench Pro 67.7 — ahead of GPT-5.6 Sol and close to Claude Opus 4.8
#2 globally on Arena.AI vision (behind only a Claude Fable 5 variant); #1 Chinese model for text
First Alibaba open-weights release at this scale — 2.4T MoE at $2/$6 per 1M
Weaknesses
Well behind Claude Fable 5 on SWE-bench Pro (67.7 vs 80.0) and behind several Anthropic models on text rankings
No independent third-party benchmarks at GA — early claims are largely Alibaba-reported
Real-world use cases
What people actually use Qwen 3.8 Max for.
Agentic coding — 67.7 SWE-bench Pro, ahead of GPT-5.6 Sol (64.6) and near Claude Opus 4.8 (69.2)
Vision-heavy pipelines: image and video understanding ranked #2 globally on Arena.AI
Large-scale deployments where 95B active params keep inference cost moderate
How Qwen 3.8 Max compares
The nearest models people weigh against it, and what actually separates them.
vs GPT-6 Astra — Against GPT-6 Astra (OpenAI), Qwen 3.8 Max runs about 87% cheaper per token, gives up 1.1x on context and answers faster. Take Qwen 3.8 Max unless you specifically need what GPT-6 Astra does better.
vs Claude Fable 5.1 — Against Claude Fable 5.1 (Anthropic), Qwen 3.8 Max runs about 87% cheaper per token and answers faster. Take Qwen 3.8 Max unless you specifically need what Claude Fable 5.1 does better.
vs Claude Fable 5 — Against Claude Fable 5 (Anthropic), Qwen 3.8 Max runs about 87% cheaper per token and answers faster. Take Qwen 3.8 Max unless you specifically need what Claude Fable 5 does better.
Price History
Qwen 3.8 Max pricing over time
→0% since Aug 7
25 data points · tracked daily since Aug 7, 2026
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Multimodal and vision-heavy workloads at scale. Start free — no card required.
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.
Verdict
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Quality score
99%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1.1M tokens
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.
Computer use leaderFrontierAgenticReasoningLong contextPremiumNew
Best for
Computer and browser use, long-horizon agentic coding, and frontier math and science work
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.
Verdict
New frontier leader — better than Fable 5 on every published benchmark, and cheaper to run.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M 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.
Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.
Verdict
Superseded by Fable 5.1 — still 80.3% SWE-Bench Pro, but 5.1 is better and cheaper to run.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses. Superseded by Claude Fable 5.1 on September 1, 2026 — same $10/$50 base pricing, cache reads cut from $1.00 to $0.25 per 1M tokens.
SWE-Bench Pro 80.3%Mythos-classParallel subagentsAgenticLong contextPremiumSuperseded
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Qwen 3.8 Max costs $2 per million input tokens and $6 per million output tokens on the API, with cached input at $0.25 per million. A month of 10M input and 2M output tokens runs about $32.00 at list price, before any batch or caching discounts.
What is the context window of Qwen 3.8 Max?
Qwen 3.8 Max has a 1M tokens context window, with up to 128k tokens of output per response. That is the total of prompt plus response the model can hold in one request.
What is Qwen 3.8 Max best for?
Qwen 3.8 Max is best for multimodal and vision-heavy workloads at scale. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and balanced speed.
When should I avoid Qwen 3.8 Max?
You need independently verified benchmarks or Western data residency.
What is a cheaper alternative to Qwen 3.8 Max?
Grok 4.5 (xAI) at $2.00/1M/1M input against Qwen 3.8 Max's $2.00/1M/1M. Best cost-per-solved-task coding agent — efficiency over ceiling. Compare it first if Qwen 3.8 Max's pricing is the thing stopping you.
What is a faster alternative to Qwen 3.8 Max?
GPT-6 Astra — deliberate against Qwen 3.8 Max's balanced, with 1.1M tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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