o4-mini vs Qwen3.5-9B
o4-mini (2025) and Qwen3.5-9B (2026) are frontier reasoning models from OpenAI and Alibaba. o4-mini ships a 200k-token context window, while Qwen3.5-9B ships a 262k-token context window. On MMLU PRO, o4-mini leads by 0.7 pts. On pricing, Qwen3.5-9B costs $0.10/1M input tokens versus $1/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Qwen3.5-9B is ~900% cheaper at $0.10/1M; pay for o4-mini only for coding workflow support.
Decision scorecard
Local evidence first| Signal | o4-mini | Qwen3.5-9B |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 200k | 262k |
| Cheapest output | $4/1M tokens | $0.15/1M tokens |
| Provider routes | 4 tracked | 3 tracked |
| Shared benchmarks | MMLU PRO leader | 3 rows |
Decision tradeoffs
- o4-mini holds a shared-benchmark lead on MMLU PRO, ahead by 0.7 points.
- o4-mini has broader tracked provider coverage for fallback and procurement flexibility.
- o4-mini uniquely exposes Reasoning and Code execution in local model data.
- Local decision data tags o4-mini for Coding, RAG, and Agents.
- Qwen3.5-9B holds a shared-benchmark lead on Google-Proof Q&A, ahead by 0.3 points.
- 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.
- Local decision data tags Qwen3.5-9B 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.
o4-mini
$1,800
Cheapest tracked route/tier: Replicate API
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $1,683. 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 $3.85/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and Code execution before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- o4-mini is $3.85/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- o4-mini adds Reasoning and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-16 | 2026-03-02 |
| Context window | 200k | 262k |
| Parameters | — | 9B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Apache 2.0(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | o4-mini | Qwen3.5-9B |
|---|---|---|
| Input price | $1/1M tokens | $0.10/1M tokens |
| Output price | $4/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | o4-mini | Qwen3.5-9B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | o4-mini | Qwen3.5-9B |
|---|---|---|
| MMLU PRO | 83.2 | 82.5 |
| Google-Proof Q&A | 81.4 | 81.7 |
| LiveCodeBench | 87.3 | 65.6 |
Deep dive
On shared benchmark coverage, MMLU PRO has o4-mini at 83.2 and Qwen3.5-9B at 82.5, with o4-mini ahead by 0.7 points; Google-Proof Q&A has o4-mini at 81.4 and Qwen3.5-9B at 81.7, with Qwen3.5-9B ahead by 0.3 points; LiveCodeBench has o4-mini at 87.3 and Qwen3.5-9B at 65.6, with o4-mini ahead by 21.7 points. The largest visible gap is 21.7 points on LiveCodeBench, 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 reasoning mode: o4-mini and code execution: o4-mini. Both models share vision, multimodal input, function calling, and tool use, 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, o4-mini lists $1/1M input and $4/1M 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 $1.78 per million blended tokens. Availability is 4 providers versus 3, so concentration risk also matters.
Choose o4-mini when coding workflow support and broader provider choice are central to the workload. Choose Qwen3.5-9B when long-context analysis, larger context windows, 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, o4-mini or Qwen3.5-9B?
Qwen3.5-9B supports 262k tokens, while o4-mini supports 200k 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, o4-mini or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. o4-mini costs $1/1M input and $4/1M 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 o4-mini or Qwen3.5-9B open source?
o4-mini is listed under Proprietary. 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, o4-mini or Qwen3.5-9B?
Both o4-mini and Qwen3.5-9B 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, o4-mini or Qwen3.5-9B?
Both o4-mini and Qwen3.5-9B 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 o4-mini and Qwen3.5-9B?
o4-mini is available on OpenAI API, OpenRouter, Replicate API, and Vercel AI Gateway. 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.