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 shared |
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 route 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 | Mixture of Experts |
| License | MITOSI-approved | Apache 2.0OSI-approved |
| Openness | Open source | Open source |
| Weights | Available | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| 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 |
| JSON / 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 |
Continue comparing
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.