Qwen3.5-397B-A17B vs Qwen3.6-27B
Qwen3.5-397B-A17B (2026) and Qwen3.6-27B (2026) compare a standalone API model against a coding-specialized model. Qwen3.5-397B-A17B ships a 262k-token context window, while Qwen3.6-27B ships a 262k-token context window. On MMLU PRO, Qwen3.5-397B-A17B leads by 1.6 pts. On pricing, Qwen3.6-27B costs $0.32/1M input tokens versus $0.39/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: Qwen3.5-397B-A17B is standalone API model, while Qwen3.6-27B is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | Qwen3.5-397B-A17B | Qwen3.6-27B |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 262k | 262k |
| Cheapest output | $2.34/1M tokens | $3.20/1M tokens |
| Provider routes | 4 tracked | 4 tracked |
| Shared benchmarks | MMLU PRO leader | 6 shared |
Decision tradeoffs
- Qwen3.5-397B-A17B holds a shared-benchmark lead on MMLU PRO, ahead by 1.6 points.
- Qwen3.5-397B-A17B has the lower cheapest tracked output price at $2.34/1M tokens.
- Qwen3.5-397B-A17B uniquely exposes Structured outputs in local model data.
- Local decision data tags Qwen3.5-397B-A17B for Coding, RAG, and Agents.
- Qwen3.6-27B holds a shared-benchmark lead on SWE-bench Verified, ahead by 1 points.
- Local decision data tags Qwen3.6-27B for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Qwen3.5-397B-A17B
$897
Cheapest tracked route/tier: OpenRouter
Qwen3.6-27B
$1,056
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $159. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI; start route-level A/B tests there.
- Qwen3.6-27B is $0.86/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- Provider overlap exists on OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI; start route-level A/B tests there.
- Qwen3.5-397B-A17B is $0.86/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-397B-A17B adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-16 | 2026-04-27 |
| Context window | 262k | 262k |
| Parameters | 397B | 27B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Apache 2.0(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Qwen3.5-397B-A17B | Qwen3.6-27B |
|---|---|---|
| Input price | $0.39/1M tokens | $0.32/1M tokens |
| Output price | $2.34/1M tokens | $3.20/1M tokens |
| Providers |
Capabilities
| Capability | Qwen3.5-397B-A17B | Qwen3.6-27B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Qwen3.5-397B-A17B | Qwen3.6-27B |
|---|---|---|
| MMLU PRO | 87.8 | 86.2 |
| SWE-bench Verified | 76.2 | 77.2 |
| Google-Proof Q&A | 89.3 | 87.8 |
| LiveCodeBench | 83.6 | 83.9 |
| Humanity's Last Exam | 28.7 | 24.0 |
| AIME 2026 | 91.3 | 94.1 |
Deep dive
On shared benchmark coverage, MMLU PRO has Qwen3.5-397B-A17B at 87.8 and Qwen3.6-27B at 86.2, with Qwen3.5-397B-A17B ahead by 1.6 points; SWE-bench Verified has Qwen3.5-397B-A17B at 76.2 and Qwen3.6-27B at 77.2, with Qwen3.6-27B ahead by 1 points; Google-Proof Q&A has Qwen3.5-397B-A17B at 89.3 and Qwen3.6-27B at 87.8, with Qwen3.5-397B-A17B ahead by 1.5 points. The largest visible gap is 1.6 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on structured outputs: Qwen3.5-397B-A17B. Both models share vision, multimodal input, reasoning mode, and function calling, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Qwen3.5-397B-A17B lists $0.39/1M input and $2.34/1M output tokens on the cheapest tracked provider, while Qwen3.6-27B lists $0.32/1M input and $3.20/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-397B-A17B lower by about $0.21 per million blended tokens. Availability is 4 providers versus 4, so concentration risk also matters.
Choose Qwen3.5-397B-A17B when vision-heavy evaluation are central to the workload. Choose Qwen3.6-27B when coding workflow support and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Qwen3.5-397B-A17B or Qwen3.6-27B?
Qwen3.5-397B-A17B supports 262k tokens, while Qwen3.6-27B supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, Qwen3.5-397B-A17B or Qwen3.6-27B?
Qwen3.5-397B-A17B is cheaper on tracked token pricing. Qwen3.5-397B-A17B costs $0.39/1M input and $2.34/1M output tokens. Qwen3.6-27B costs $0.32/1M input and $3.20/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Qwen3.5-397B-A17B or Qwen3.6-27B open source?
Qwen3.5-397B-A17B is listed under Apache 2.0. Qwen3.6-27B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Qwen3.5-397B-A17B or Qwen3.6-27B?
Both Qwen3.5-397B-A17B and Qwen3.6-27B expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Qwen3.5-397B-A17B or Qwen3.6-27B?
Both Qwen3.5-397B-A17B and Qwen3.6-27B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Qwen3.5-397B-A17B and Qwen3.6-27B?
Qwen3.5-397B-A17B is available on OpenRouter, Together AI, Alibaba Cloud PAI-EAS, and Novita AI. Qwen3.6-27B is available on OpenRouter, Alibaba Cloud PAI-EAS, Vercel AI Gateway, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.