Qwen3.5 397B A17B vs DeepSeek V3.2
At a Glance
| Compare |  DeepSeek V3.2DeepSeek | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.45Deepinfra ↗ · Sep 22, 2026 | $0.26Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $3.00Deepinfra ↗ · Sep 22, 2026 | $0.38Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 262K | 164K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Qwen3.5-397B-A17B | DeepSeek-V3.2 |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,438.26100% of row best · rating · qwen3.5-397b-a17b; 95% CI [1434.97391785, 1441.55191176]; votes 77007; rank 71 | 1,424.8099% of row best · rating · deepseek-v3.2; 95% CI [1421.27271719, 1428.32733406]; votes 46458; rank 96 |
| Overall ResultCounted from the protocol-matched rows above | 1 benchmark winNo overall winner | 0 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Qwen3.5-397B-A17B | DeepSeek-V3.2 |
|---|---|---|
| Developer | Qwen | DeepSeek |
| Family | Qwen3 5 397b A17b | Deepseek V3 2 |
| Model | Qwen3.5-397B-A17B | DeepSeek-V3.2 |
| Version | Qwen3.5-397B-A17B | DeepSeek-V3.2 |
| Lifecycle | active | active |
| Released | 2026-02-15 | 2025-12-01 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 262K | 164K |
| Total parameters | 403.4B | 685.4B |
| Active parameters | 17B | Unknown |
| 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) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning |
Qwen3.5 397B A17B Capabilities
DeepSeek V3.2 Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
| vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text | |
| vs | Claude Fable 5.1Anthropic | cross-developer peersimage, text | |
| vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext | |
| vs | DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text | |
| vs | Grok 4.6xAI | cross-developer peersimage, text | |
| vs |  Qwen3.8-MaxQwen | family variantsimage, text | |
| vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text | |
 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 |
Primary Evidence
Sources and Freshness
Questions
Qwen3.5 397B A17B vs DeepSeek V3.2 FAQs
Is Qwen3.5 397B A17B or DeepSeek V3.2 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 397B A17B and DeepSeek V3.2, 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 V3.2?+
Qwen3.5 397B A17B is $0.45 and DeepSeek V3.2 is $0.26 per million tokens, so DeepSeek V3.2 is cheaper on this metric. Qwen3.5 397B A17B is $3.00 and DeepSeek V3.2 is $0.38 per million tokens, so DeepSeek V3.2 is cheaper on this metric.
Which has a larger context window, Qwen3.5 397B A17B or DeepSeek V3.2?+
Qwen3.5 397B A17B has the larger sourced context window. Qwen3.5 397B A17B supports 262K and DeepSeek V3.2 supports 164K.
Which performs better in benchmarks, Qwen3.5 397B A17B or DeepSeek V3.2?+
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 V3.2 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.5 397B A17B is open weight; DeepSeek V3.2 is open weight.
Can Qwen3.5 397B A17B and DeepSeek V3.2 understand images?+
Qwen3.5 397B A17B is documented with image input; DeepSeek V3.2 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 V3.2?+
Neither has a larger sourced maximum output. Qwen3.5 397B A17B is — and DeepSeek V3.2 is —.
Do Qwen3.5 397B A17B and DeepSeek V3.2 support reasoning and tool use?+
Qwen3.5 397B A17B: reasoning, tool calling, and image input. DeepSeek V3.2: reasoning. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.5 397B A17B or DeepSeek V3.2?+
Qwen3.5 397B A17B has 4 sourced provider routes; DeepSeek V3.2 has 3, so Qwen3.5 397B A17B has broader tracked availability.
Which offers better value, Qwen3.5 397B A17B or DeepSeek V3.2?+
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.