Qwen3.5 397B A17B vs Ministral 3 14B Instruct 2512
At a Glance
| Compare |  Ministral 3 14B Instruct 2512Mistral AI | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.45Deepinfra ↗ · Sep 21, 2026 | $0.20Openrouter ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $3.00Deepinfra ↗ · Sep 21, 2026 | $0.20Openrouter ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 262K | 262K |
| 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
Side-by-Side Facts
| Field | Qwen3.5-397B-A17B | Ministral-3-14B-Instruct-2512 |
|---|---|---|
| Developer | Qwen | Mistral AI |
| Family | Qwen3 5 397b A17b | Ministral 3 14b Instruct 2512 |
| Model | Qwen3.5-397B-A17B | Ministral-3-14B-Instruct-2512 |
| Version | Qwen3.5-397B-A17B | Ministral-3-14B-Instruct-2512 |
| Lifecycle | active | active |
| Released | 2026-02-15 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 262K | 262K |
| Total parameters | 403.4B | 13.9B |
| Active parameters | 17B | Unknown |
| License | apache-2.0 | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, tools |
Qwen3.5 397B A17B Capabilities
Ministral 3 14B Instruct 2512 Capabilities
Related Comparisons
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| 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 Ministral 3 14B Instruct 2512 FAQs
Is Qwen3.5 397B A17B or Ministral 3 14B Instruct 2512 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 397B A17B and Ministral 3 14B Instruct 2512, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.5 397B A17B or Ministral 3 14B Instruct 2512?+
Qwen3.5 397B A17B is $0.45 and Ministral 3 14B Instruct 2512 is $0.20 per million tokens, so Ministral 3 14B Instruct 2512 is cheaper on this metric. Qwen3.5 397B A17B is $3.00 and Ministral 3 14B Instruct 2512 is $0.20 per million tokens, so Ministral 3 14B Instruct 2512 is cheaper on this metric.
Which has a larger context window, Qwen3.5 397B A17B or Ministral 3 14B Instruct 2512?+
Neither model has a larger sourced context window in this comparison. Qwen3.5 397B A17B is 262K and Ministral 3 14B Instruct 2512 is 262K.
Which performs better in benchmarks, Qwen3.5 397B A17B or Ministral 3 14B Instruct 2512?+
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 Ministral 3 14B Instruct 2512 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.5 397B A17B is open weight; Ministral 3 14B Instruct 2512 is open weight.
Can Qwen3.5 397B A17B and Ministral 3 14B Instruct 2512 understand images?+
Qwen3.5 397B A17B is documented with image input; Ministral 3 14B Instruct 2512 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.5 397B A17B or Ministral 3 14B Instruct 2512?+
Neither has a larger sourced maximum output. Qwen3.5 397B A17B is — and Ministral 3 14B Instruct 2512 is —.
Do Qwen3.5 397B A17B and Ministral 3 14B Instruct 2512 support reasoning and tool use?+
Qwen3.5 397B A17B: reasoning, tool calling, and image input. Ministral 3 14B Instruct 2512: tool calling and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.5 397B A17B or Ministral 3 14B Instruct 2512?+
Qwen3.5 397B A17B has 4 sourced provider routes; Ministral 3 14B Instruct 2512 has 2, so Qwen3.5 397B A17B has broader tracked availability.
Which offers better value, Qwen3.5 397B A17B or Ministral 3 14B Instruct 2512?+
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.