Qwen 3.8 Flash wins on price ($0.16 vs $2/1M input). Qwen 3.8 Max wins on coding (93 vs 84) and writing quality. For most workflows, Qwen 3.8 Max is the stronger default — best chinese flagship — beats gpt-5.6 sol on coding, #2 globally for vision.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
Qwen 3.8 Max is the safest overall answer here when you want the strongest default instead of the lowest list price.
Mistral: Mistral Nemo is the lower-cost option to start with when you still need useful output at scale.
Qwen 3.8 Flash is the better pick when response speed matters more than maximum reasoning depth.
Qwen 3.8 Max leads on coding with a score of 93 vs 84 for Qwen 3.8 Flash.
Qwen 3.8 Max has the larger context window: 1M vs 991K for Qwen 3.8 Flash.
Qwen 3.8 Flash is cheaper at $0.16/1M input tokens vs $2/1M for Qwen 3.8 Max.
Qwen 3.8 Max is the safer default: it is built for multimodal and vision-heavy workloads at scale, which covers most of what people bring to this comparison.
Choose Qwen 3.8 Flash when your work is mostly cheap high-throughput coding and reasoning — that is the workload it was tuned for.
Qwen 3.8 Flash is the more cost-efficient option at $0.16/1M input — Qwen 3.8 Max costs 13x more per input token, so the gap is worth taking seriously wherever token volume rather than peak quality drives the bill.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
Alibaba / Balanced / Aug 6, 2026
Best Chinese flagship — beats GPT-5.6 Sol on coding, #2 globally for vision.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need independently verified benchmarks or Western data residency.
The fastest way to see where the recommendation shifts when your priority changes.
SWE-bench Pro 62.5 at sixteen cents per million input.
Best Chinese flagship — beats GPT-5.6 Sol on coding, #2 globally for vision.
Every figure below is the provider's list price or a published capability score — the same numbers the recommendation on this page is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Qwen 3.8 MaxAlibaba | $2.00/1M | $6.00/1M | $32 | 1M tokens | Balanced | 93 | 85 | 88 |
| Qwen 3.8 FlashAlibaba | $0.16/1M | $0.47/1M | $2.54 | 991k tokens | Very fast | 84 | 76 | 78 |
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.
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.
Alibaba's largest model ever — a 2.4-trillion-parameter MoE (95B active) multimodal flagship that beat GPT-5.6 Sol on SWE-bench Pro and ranks #2 globally for vision.
You need independently verified benchmarks or Western data residency.
The strongest Chinese multimodal flagship and a legitimate SWE-bench Pro upset over GPT-5.6 Sol. If vision matters, only Fable 5-class models beat it — at 3–8x the price. Wait for independent evals before betting production on the self-reported numbers.
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.
Alibaba's preview of the Qwen4 architecture — 125B parameters with only 6B active per token, at sixteen cents per million input.
You need Alibaba's maximum capability — that is Qwen 3.8 Max — or a SWE-bench Verified number.
One of the best coding-score-per-dollar picks in the catalog. Route volume work here and reserve Qwen 3.8 Max or a frontier model for the hard cases.
Released August 26, 2026. The open-weight release is Qwen3.8-Flash-Next, a preview of the Qwen4 architecture: 125B mixture-of-experts with 6B active per token, a 51B n-gram embedding table and a 4B multi-token prediction layer. Qwen 3.8 Flash is the production API version on Qwen Cloud at $0.16/$0.47.
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Qwen 3.8 Max wins on more of the categories we score — coding, multimodal, reasoning — so it is the better default of the two. Qwen 3.8 Flash is the better pick when your work is mostly cheap high-throughput coding and reasoning. Neither is universally "better": Qwen 3.8 Max is aimed at multimodal and vision-heavy workloads at scale, Qwen 3.8 Flash at cheap high-throughput coding and reasoning.
Qwen 3.8 Flash is cheaper at $0.16/1M input and $0.47/1M output. Qwen 3.8 Max costs $2/1M input and $6/1M output.
Qwen 3.8 Max has the larger context window at 1M tokens vs Qwen 3.8 Flash's 991K. For large document analysis, Qwen 3.8 Max is the stronger pick.
Qwen 3.8 Max is better for coding with a score of 93 vs Qwen 3.8 Flash's 84 (out of 100). Claude Fable 5 is the overall coding leader in this directory at 100/100.
Qwen 3.8 Flash is faster with a very fast speed rating (score: 5) vs Qwen 3.8 Max's balanced rating (score: 3). Speed matters most for interactive and high-throughput work; for batch jobs the Qwen 3.8 Max latency penalty is usually invisible.
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. Avoid it if you need independently verified benchmarks or Western data residency. That is the main case for looking at Qwen 3.8 Flash instead.
No published SWE-bench Verified score, only SWE-bench Pro. An architecture preview rather than a settled flagship — Qwen 3.8 Max remains Alibaba's top-end model. Avoid it if you need Alibaba's maximum capability — that is Qwen 3.8 Max — or a SWE-bench Verified number. Against Qwen 3.8 Max specifically, the gap shows up most on coding (93 vs 84).
Take a moderate workload of 10M input and 2M output tokens a month. Qwen 3.8 Flash runs $2.54 (at $0.16/1M in and $0.47/1M out); Qwen 3.8 Max runs $32.00 (at $2/1M in and $6/1M out). That is a $29.46/month difference — Qwen 3.8 Flash is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is Qwen 3.8 Max for multimodal and vision-heavy workloads at scale, with Qwen 3.8 Flash handling cheap high-throughput coding and reasoning. Routing high-volume, low-stakes calls to Qwen 3.8 Flash at $0.16/1M and reserving Qwen 3.8 Max for the hard cases is usually the cheapest arrangement that does not cost you quality.