DeepSeek V4 Pro vs Qwen3.5-9B
DeepSeek V4 Pro (2026) and Qwen3.5-9B (2026) are frontier reasoning models from DeepSeek and Alibaba. DeepSeek V4 Pro ships a 1M-token context window, while Qwen3.5-9B ships a 262K-token context window. On MMLU PRO, DeepSeek V4 Pro leads by 5 pts. On pricing, Qwen3.5-9B costs $0.10/1M input tokens versus $0.43/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3.5-9B is ~335% cheaper at $0.10/1M; pay for DeepSeek V4 Pro only for reasoning depth.
Decision scorecard
Local evidence first| Signal | DeepSeek V4 Pro | Qwen3.5-9B |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Agents, and Long context |
| Context window | 1M | 262K |
| Cheapest output | $0.87/1M tokens | $0.15/1M tokens |
| Provider routes | 5 tracked | 3 tracked |
| Shared benchmarks | MMLU PRO leader | 2 rows |
Decision tradeoffs
- DeepSeek V4 Pro leads the largest shared benchmark signal on MMLU PRO by 5 points.
- DeepSeek V4 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek V4 Pro has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek V4 Pro uniquely exposes Reasoning in local model data.
- Local decision data tags DeepSeek V4 Pro for Coding, RAG, and Agents.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B uniquely exposes Vision and Multimodal 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.
DeepSeek V4 Pro
$566
Cheapest tracked route/tier: DeepSeek Platform
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $448. 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 $0.72/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning before moving production traffic.
- Qwen3.5-9B adds Vision and Multimodal in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- DeepSeek V4 Pro is $0.72/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- DeepSeek V4 Pro adds Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-24 | 2026-03-02 |
| Context window | 1M | 262K |
| Parameters | 1.6T | 9B |
| Architecture | Mixture of Experts (MoE) with CSA+HCA hybrid attention | decoder only |
| License | MIT | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V4 Pro | Qwen3.5-9B |
|---|---|---|
| Input price | $0.43/1M tokens | $0.10/1M tokens |
| Output price | $0.87/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V4 Pro | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V4 Pro | Qwen3.5-9B |
|---|---|---|
| MMLU PRO | 87.5 | 82.5 |
| Google-Proof Q&A | 90.1 | 81.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek V4 Pro at 87.5 and Qwen3.5-9B at 82.5, with DeepSeek V4 Pro ahead by 5 points; Google-Proof Q&A has DeepSeek V4 Pro at 90.1 and Qwen3.5-9B at 81.7, with DeepSeek V4 Pro ahead by 8.4 points. The largest visible gap is 8.4 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, and reasoning mode: DeepSeek V4 Pro. Both models share function calling, tool use, and 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, DeepSeek V4 Pro lists $0.43/1M input and $0.87/1M 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 $0.45 per million blended tokens. Availability is 5 providers versus 3, so concentration risk also matters.
Choose DeepSeek V4 Pro when reasoning depth, larger context windows, and broader provider choice are central to the workload. Choose Qwen3.5-9B when vision-heavy evaluation 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, DeepSeek V4 Pro or Qwen3.5-9B?
DeepSeek V4 Pro supports 1M tokens, while Qwen3.5-9B supports 262K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, DeepSeek V4 Pro or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. DeepSeek V4 Pro costs $0.43/1M input and $0.87/1M 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 DeepSeek V4 Pro or Qwen3.5-9B open source?
DeepSeek V4 Pro is listed under MIT. 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, DeepSeek V4 Pro 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, DeepSeek V4 Pro 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 DeepSeek V4 Pro and Qwen3.5-9B?
DeepSeek V4 Pro is available on DeepSeek Platform, Fireworks AI, OpenRouter, Vercel AI Gateway, 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.