Qwen3-235B-A22B vs Qwen3.5-9B
Qwen3-235B-A22B (2025) and Qwen3.5-9B (2026) are compact production models from Alibaba. Qwen3-235B-A22B ships a 128k-token context window, while Qwen3.5-9B ships a 262k-token context window. On MMLU PRO, Qwen3-235B-A22B leads by a hair. On pricing, Qwen3-235B-A22B costs $0.09/1M input tokens versus $0.10/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.5-9B is safer overall; choose Qwen3-235B-A22B when provider fit matters.
Decision scorecard
Local evidence first| Signal | Qwen3-235B-A22B | Qwen3.5-9B |
|---|---|---|
| Best for | provider-routed production | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Long context | RAG, Agents, and Long context |
| Context window | 128k | 262k |
| Cheapest output | $0.58/1M tokens | $0.15/1M tokens |
| Provider routes | 7 tracked | 3 tracked |
| Shared benchmarks | MMLU PRO leader | 2 rows |
Decision tradeoffs
- Qwen3-235B-A22B leads the largest shared benchmark signal on MMLU PRO by 0.3 points.
- Qwen3-235B-A22B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Qwen3-235B-A22B for Coding, RAG, and Long context.
- Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Qwen3-235B-A22B
$217
Cheapest tracked route/tier: Novita AI
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $99.50. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3.5-9B is $0.43/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-9B adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3-235B-A22B is $0.43/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-29 | 2026-03-02 |
| Context window | 128k | 262k |
| Parameters | 235B | 9B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Qwen3-235B-A22B | Qwen3.5-9B |
|---|---|---|
| Input price | $0.09/1M tokens | $0.10/1M tokens |
| Output price | $0.58/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Qwen3-235B-A22B | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Qwen3-235B-A22B | Qwen3.5-9B |
|---|---|---|
| MMLU PRO | 82.8 | 82.5 |
| Google-Proof Q&A | 86.1 | 81.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has Qwen3-235B-A22B at 82.8 and Qwen3.5-9B at 82.5, with Qwen3-235B-A22B ahead by 0.3 points; Google-Proof Q&A has Qwen3-235B-A22B at 86.1 and Qwen3.5-9B at 81.7, with Qwen3-235B-A22B ahead by 4.4 points. The largest visible gap is 4.4 points on Google-Proof Q&A, 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 vision: Qwen3.5-9B, multimodal input: Qwen3.5-9B, function calling: Qwen3.5-9B, and tool use: Qwen3.5-9B. Both models share structured outputs, 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, Qwen3-235B-A22B lists $0.09/1M input and $0.58/1M output tokens on the cheapest tracked provider, while Qwen3.5-9B lists $0.10/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-9B lower by about $0.12 per million blended tokens. Availability is 7 providers versus 3, so concentration risk also matters.
Choose Qwen3-235B-A22B when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen3.5-9B when long-context analysis and larger context windows 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, Qwen3-235B-A22B or Qwen3.5-9B?
Qwen3.5-9B supports 262k tokens, while Qwen3-235B-A22B supports 128k 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, Qwen3-235B-A22B or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. Qwen3-235B-A22B costs $0.09/1M input and $0.58/1M output tokens. Qwen3.5-9B costs $0.10/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Qwen3-235B-A22B or Qwen3.5-9B open source?
Qwen3-235B-A22B is listed under Apache 2.0. Qwen3.5-9B 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, Qwen3-235B-A22B or Qwen3.5-9B?
Qwen3.5-9B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Qwen3-235B-A22B or Qwen3.5-9B?
Qwen3.5-9B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Qwen3-235B-A22B and Qwen3.5-9B?
Qwen3-235B-A22B is available on Fireworks AI, AWS Bedrock, OpenRouter, Venice AI, and Novita AI. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.