Qwen3.5 35B A3B vs Codestral 22B v0.1
At a Glance
| Compare |  Qwen3.5 35B A3BQwen |  Codestral 22B v0.1Mistral AI |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.14Deepinfra ↗ · Sep 21, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $1.00Deepinfra ↗ · Sep 21, 2026 | Not reported |
| Context windowMaximum documented tokens | 262K | 33K |
| 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 | Qwen3.5-35B-A3B | Codestral-22B-v0.1 |
|---|---|---|
| Developer | Qwen | Mistral AI |
| Family | Qwen3 5 35b A3b | Codestral 22b V0 1 |
| Model | Qwen3.5-35B-A3B | Codestral-22B-v0.1 |
| Version | Qwen3.5-35B-A3B | Codestral-22B-v0.1 |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 262K | 33K |
| Total parameters | 36B | 22.2B |
| Active parameters | 3B | Unknown |
| License | apache-2.0 | other |
| Open weights | Yes | Yes |
| API available | Yes | Unknown |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, tools | generation |
Qwen3.5 35B A3B Capabilities
Codestral 22B v0.1 Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
Qwen3.5-35B-A3BQwen | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs | Claude Fable 5.1Anthropic | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Qwen3.5-35B-A3BQwen | vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs | Grok 4.6xAI | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs | Qwen3.8-MaxQwen | family variantsimage, text |
Qwen3.5-35B-A3BQwen | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Qwen3.5-35B-A3BQwen | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Qwen3.5-35B-A3BQwen | vs |  Hy4 previewTencent | cross-developer peerstext |
Qwen3.5-35B-A3BQwen | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs | Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Qwen3.5 35B A3B vs Codestral 22B v0.1 FAQs
Is Qwen3.5 35B A3B or Codestral 22B v0.1 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 35B A3B and Codestral 22B v0.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.5 35B A3B or Codestral 22B v0.1?+
Only Qwen3.5 35B A3B has a directly sourced input price: $0.14 per million tokens. Only Qwen3.5 35B A3B has a directly sourced output price: $1.00 per million tokens.
Which has a larger context window, Qwen3.5 35B A3B or Codestral 22B v0.1?+
Qwen3.5 35B A3B has the larger sourced context window. Qwen3.5 35B A3B supports 262K and Codestral 22B v0.1 supports 33K.
Which performs better in benchmarks, Qwen3.5 35B A3B or Codestral 22B v0.1?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.5 35B A3B or Codestral 22B v0.1 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.5 35B A3B is open weight; Codestral 22B v0.1 is open weight.
Can Qwen3.5 35B A3B and Codestral 22B v0.1 understand images?+
Qwen3.5 35B A3B is documented with image input; Codestral 22B v0.1 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.5 35B A3B or Codestral 22B v0.1?+
Neither has a larger sourced maximum output. Qwen3.5 35B A3B is — and Codestral 22B v0.1 is —.
Do Qwen3.5 35B A3B and Codestral 22B v0.1 support reasoning and tool use?+
Qwen3.5 35B A3B: reasoning, tool calling, and image input. Codestral 22B v0.1: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.5 35B A3B or Codestral 22B v0.1?+
Qwen3.5 35B A3B has 4 sourced provider routes; Codestral 22B v0.1 has 0, so Qwen3.5 35B A3B has broader tracked availability.
Which offers better value, Qwen3.5 35B A3B or Codestral 22B v0.1?+
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.