Qwen3.5 397B A17B vs DeepSeek V4 Pro
Model Markets Rankings
Intelligence, Cost, and Efficiency
| Ranking | Qwen3.5-397B-A17B | DeepSeek-V4-Pro |
|---|---|---|
| CostLower is better · Published-token output estimate | UnrankedNot in the 36-model eligible cohort | #9 of 36$0.054 per LiveBench case |
Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.
Benchmark Performance
Available Benchmarks
| Benchmark | Qwen3.5-397B-A17B | DeepSeek-V4-Pro |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,437.8499% of row best · rating · qwen3.5-397b-a17b; 95% CI [1434.48605524, 1441.19621255]; votes 73400; rank 68 | 1,451.00100% of row best · rating · deepseek-v4-pro; 95% CI [1447.00829245, 1454.98663953]; votes 54243; rank 41 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark wins | 1 benchmark winOverall lead |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | Qwen3.5-397B-A17B | DeepSeek-V4-Pro |
|---|---|---|
| Developer | Qwen | DeepSeek |
| Family | Qwen3 5 397b A17b | Deepseek V4 Pro |
| Model | Qwen3.5-397B-A17B | DeepSeek-V4-Pro |
| Version | Qwen3.5-397B-A17B | DeepSeek-V4-Pro |
| Lifecycle | active | active |
| Released | 2026-02-15 | 2026-04-24 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 262K | 1,049K |
| Total parameters | 403.4B | 1.6T |
| Active parameters | 17B | 49B |
| License | apache-2.0 | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | DeepSeek (Standard), Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning |
17 comparable fields · 12 material differences · Pair passes the primary-source comparison gate
Qwen3.5 397B A17B Capabilities
DeepSeek V4 Pro Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
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| vs | Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext | |
| vs | Grok 4.6xAI | cross-developer peersimage, text | |
| vs | Qwen3.8-MaxQwen | family variantsimage, text | |
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MiniMax-M3MiniMax | vs | cross-developer peersimage, text | |
| vs | GLM-5.3Z.ai | cross-developer peerstext | |
| vs | Hy4 previewTencent | cross-developer peerstext | |
| vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text | |
| vs | Mistral Large 3Mistral AI | cross-developer peersimage, text | |
| vs | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Qwen3.5 397B A17B vs DeepSeek V4 Pro FAQs
Is Qwen3.5 397B A17B or DeepSeek V4 Pro better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 397B A17B and DeepSeek V4 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.5 397B A17B or DeepSeek V4 Pro?+
Qwen3.5 397B A17B is $0.45 and DeepSeek V4 Pro is $0.66 per million tokens, so Qwen3.5 397B A17B is cheaper on this metric. Qwen3.5 397B A17B is $3.00 and DeepSeek V4 Pro is $1.5441 per million tokens, so DeepSeek V4 Pro is cheaper on this metric.
Which has a larger context window, Qwen3.5 397B A17B or DeepSeek V4 Pro?+
DeepSeek V4 Pro has the larger sourced context window. Qwen3.5 397B A17B supports 262K and DeepSeek V4 Pro supports 1,049K.
Which performs better in benchmarks, Qwen3.5 397B A17B or DeepSeek V4 Pro?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.5 397B A17B or DeepSeek V4 Pro be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.5 397B A17B is open weight; DeepSeek V4 Pro is open weight.
Can Qwen3.5 397B A17B and DeepSeek V4 Pro understand images?+
Qwen3.5 397B A17B is documented with image input; DeepSeek V4 Pro is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.5 397B A17B or DeepSeek V4 Pro?+
Neither has a larger sourced maximum output. Qwen3.5 397B A17B is — and DeepSeek V4 Pro is —.
Do Qwen3.5 397B A17B and DeepSeek V4 Pro support reasoning and tool use?+
Qwen3.5 397B A17B: reasoning, tool calling, and image input. DeepSeek V4 Pro: reasoning. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.5 397B A17B or DeepSeek V4 Pro?+
Qwen3.5 397B A17B has 4 sourced provider routes; DeepSeek V4 Pro has 6, so DeepSeek V4 Pro has broader tracked availability.
Which offers better value, Qwen3.5 397B A17B or DeepSeek V4 Pro?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.