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 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.
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 Opus 4.7 — Against Claude Opus 4.7 (Anthropic), Qwen 3.8 Max runs about 73% cheaper per token and answers faster. Take Qwen 3.8 Max unless you specifically need what Claude Opus 4.7 does better.
Price History
Qwen 3.8 Max pricing over time
→0% since Aug 7
38 data points · tracked daily since Aug 7, 2026
Ready to try it?
Start using Qwen 3.8 Max
Multimodal and vision-heavy workloads at scale. Start free — no card required.
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
New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.
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.
Coding leaderSWE-Bench Pro #1Mythos-classParallel subagentsAgenticLong contextPremiumNew
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
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.
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?
GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against Qwen 3.8 Max's $2.00/1M/1M. The strongest choice for serious software engineering work, provided you can absorb the output-side pricing. 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?
Claude Fable 5 — deliberate against Qwen 3.8 Max's balanced, with 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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