Qwen 3.8 Flash wins on coding (84 vs 80) and price ($0.16 vs $0.35/1M input) and context window (991K vs 131K). For most workflows, Qwen 3.8 Flash is the stronger default — swe-bench pro 62.5 at sixteen cents per million input.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
Qwen 3.8 Flash 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.
Muse Glimmer 30B is the better pick when response speed matters more than maximum reasoning depth.
Qwen 3.8 Flash leads on coding with a score of 84 vs 80 for Muse Glimmer 30B.
Qwen 3.8 Flash has the larger context window: 991K vs 131K for Muse Glimmer 30B.
Qwen 3.8 Flash is cheaper at $0.16/1M input tokens vs $0.35/1M for Muse Glimmer 30B.
Go with Qwen 3.8 Flash if you want one model to handle budget and coding — it targets cheap high-throughput coding and reasoning.
Switch to Muse Glimmer 30B when your work is mostly local and self-hosted agents that run continuously; on that narrower brief it is the better tool.
Both models serve different primary workflows — Qwen 3.8 Flash for cheap high-throughput coding and reasoning, Muse Glimmer 30B for local and self-hosted agents that run continuously — so running each where it has a clear edge often beats forcing one to do both.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
Alibaba / Budget / Aug 27, 2026
SWE-bench Pro 62.5 at sixteen cents per million input.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need Alibaba's maximum capability — that is Qwen 3.8 Max — or a SWE-bench Verified number.
The fastest way to see where the recommendation shifts when your priority changes.
Apache 2.0 agent model that runs on a 24GB GPU.
SWE-bench Pro 62.5 at sixteen cents per million input.
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 FlashAlibaba | $0.16/1M | $0.47/1M | $2.54 | 991k tokens | Very fast | 84 | 76 | 78 |
| Muse Glimmer 30BMeta | $0.35/1M | $1.50/1M | $6.50 | 131k tokens | Fast | 80 | 74 | 76 |
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 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.
Meta's return to genuine open source — a 30B dense model under Apache 2.0, built for always-on agents rather than chat, and the first release from Meta Superintelligence Labs.
You need a large context window or the strongest agent scores at this size — check Qwen's 27B first.
The best Apache 2.0 agent model you can run on consumer hardware right now. Pick it when licence freedom and local execution matter more than the last few benchmark points — otherwise Qwen3.6-27B edges it on agent tasks.
Released August 9, 2026 — the first model from Meta Superintelligence Labs and Meta's return to a genuinely permissive licence. No Meta API price; hosted rates from third parties such as Together and OpenRouter land around $0.35/$1.50. Local hardware targets: 24GB for K-Quant-17GB, 32GB for K-Quant-Dynamic, 64GB for full precision.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Qwen 3.8 Flash wins on more of the categories we score — budget, coding, reasoning — so it is the better default of the two. Muse Glimmer 30B is the better pick when your work is mostly local and self-hosted agents that run continuously. Neither is universally "better": Qwen 3.8 Flash is aimed at cheap high-throughput coding and reasoning, Muse Glimmer 30B at local and self-hosted agents that run continuously.
Qwen 3.8 Flash is cheaper at $0.16/1M input and $0.47/1M output. Muse Glimmer 30B costs $0.35/1M input and $1.5/1M output.
Qwen 3.8 Flash has the larger context window at 991K tokens vs Muse Glimmer 30B's 131K. For large document analysis, Qwen 3.8 Flash is the stronger pick.
Qwen 3.8 Flash is better for coding with a score of 84 vs Muse Glimmer 30B's 80 (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 Muse Glimmer 30B's fast rating (score: 4). Speed matters most for interactive and high-throughput work; for batch jobs the Muse Glimmer 30B latency penalty is usually invisible.
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. That is the main case for looking at Muse Glimmer 30B instead.
Qwen3.6-27B beats it on several practical agent and multimodal tests in Meta's own comparison table. Meta publishes no first-party API price — you pay a third-party host or run it yourself. 131K context is small next to the 1M-token field. Avoid it if you need a large context window or the strongest agent scores at this size — check Qwen's 27B first. Against Qwen 3.8 Flash specifically, the gap shows up most on coding (84 vs 80).
Take a moderate workload of 10M input and 2M output tokens a month. Muse Glimmer 30B runs $6.50 (at $0.35/1M in and $1.5/1M out); Qwen 3.8 Flash runs $2.54 (at $0.16/1M in and $0.47/1M out). That is a $3.96/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 Flash for cheap high-throughput coding and reasoning, with Muse Glimmer 30B handling local and self-hosted agents that run continuously. Since Qwen 3.8 Flash is both the stronger and the cheaper option here, a split mainly makes sense if Muse Glimmer 30B covers a capability you specifically need.