DeepSeek V4 Pro vs Qwen3.5-122B-A10B
DeepSeek V4 Pro (2026) and Qwen3.5-122B-A10B (2026) are frontier-tier reasoning models from DeepSeek and Alibaba. DeepSeek V4 Pro ships a 1m-token context window, while Qwen3.5-122B-A10B ships a 262k-token context window. On MMLU PRO, DeepSeek V4 Pro leads by 0.8 pts. On pricing, Qwen3.5-122B-A10B costs $0.26/1M input tokens versus $0.43/1M 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.
Qwen3.5-122B-A10B is ~67% cheaper at $0.26/1M; pay for DeepSeek V4 Pro only for long-context analysis.
Decision scorecard
Local evidence first| Signal | DeepSeek V4 Pro | Qwen3.5-122B-A10B |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 262k |
| Cheapest output | $0.87/1M tokens | $2.08/1M tokens |
| Provider routes | 5 tracked | 3 tracked |
| Shared benchmarks | MMLU PRO leader | 6 rows |
Decision tradeoffs
- DeepSeek V4 Pro holds a shared-benchmark lead on MMLU PRO, ahead by 0.8 points.
- DeepSeek V4 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek V4 Pro has the lower cheapest tracked output price at $0.87/1M tokens.
- DeepSeek V4 Pro has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags DeepSeek V4 Pro for Coding, RAG, and Agents.
- Qwen3.5-122B-A10B uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Qwen3.5-122B-A10B 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.
DeepSeek V4 Pro
$566
Cheapest tracked route/tier: DeepSeek Platform
Qwen3.5-122B-A10B
$728
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $163. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- Qwen3.5-122B-A10B is $1.21/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.5-122B-A10B adds Vision and Multimodal in local capability data.
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- DeepSeek V4 Pro is $1.21/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-24 | 2026-02-24 |
| Context window | 1m | 262k |
| Parameters | 1.6T | 122B |
| Architecture | Mixture of Experts (MoE) with CSA+HCA hybrid attention | mixture of experts |
| License | MIT(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 | DeepSeek V4 Pro | Qwen3.5-122B-A10B |
|---|---|---|
| Input price | $0.43/1M tokens | $0.26/1M tokens |
| Output price | $0.87/1M tokens | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V4 Pro | Qwen3.5-122B-A10B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | Yes |
| 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 | Qwen3.5-122B-A10B |
|---|---|---|
| MMLU PRO | 87.5 | 86.7 |
| SWE-bench Verified | 80.6 | 72.0 |
| Google-Proof Q&A | 90.1 | 85.7 |
| LiveCodeBench | 93.5 | 78.9 |
| Humanity's Last Exam | 37.7 | 25.3 |
| BrowseComp | 83.4 | 63.8 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek V4 Pro at 87.5 and Qwen3.5-122B-A10B at 86.7, with DeepSeek V4 Pro ahead by 0.8 points; SWE-bench Verified has DeepSeek V4 Pro at 80.6 and Qwen3.5-122B-A10B at 72, with DeepSeek V4 Pro ahead by 8.6 points; Google-Proof Q&A has DeepSeek V4 Pro at 90.1 and Qwen3.5-122B-A10B at 85.7, with DeepSeek V4 Pro ahead by 4.4 points. The largest visible gap is 8.6 points on SWE-bench Verified, 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: Qwen3.5-122B-A10B and multimodal input: Qwen3.5-122B-A10B. Both models share reasoning mode, 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 Qwen3.5-122B-A10B lists $0.26/1M input and $2.08/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V4 Pro lower by about $0.24 per million blended tokens. Availability is 5 providers versus 3, so concentration risk also matters.
Choose DeepSeek V4 Pro when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B?
DeepSeek V4 Pro supports 1m tokens, while Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B?
DeepSeek V4 Pro is cheaper on tracked token pricing. DeepSeek V4 Pro costs $0.43/1M input and $0.87/1M output tokens. Qwen3.5-122B-A10B costs $0.26/1M input and $2.08/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V4 Pro or Qwen3.5-122B-A10B open source?
DeepSeek V4 Pro is listed under MIT. Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B?
DeepSeek V4 Pro is available on DeepSeek Platform, Fireworks AI, OpenRouter, Vercel AI Gateway, and Novita AI. Qwen3.5-122B-A10B is available on OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-31. Data sourced from public model cards and provider documentation.