Claude Haiku 4.5 vs Codestral 22B v0.1
At a Glance
| Compare | Claude Haiku 4.5Anthropic |  Codestral 22B v0.1Mistral AI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #43 of 469.0 score · 2/3 sources · provisional · missing LiveBench · full-core range 6.0–39.3 | UnrankedNot in the 46-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $1.00Anthropic ↗ · Sep 3, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $5.00Anthropic ↗ · Sep 3, 2026 | Not reported |
| Context windowMaximum documented tokens | 200K | 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 | Claude Haiku 4.5 | Codestral-22B-v0.1 |
|---|---|---|
| Developer | Anthropic | Mistral AI |
| Family | Claude 4 5 | Codestral 22b V0 1 |
| Model | Claude Haiku 4.5 | Codestral-22B-v0.1 |
| Version | Claude Haiku 4.5 | Codestral-22B-v0.1 |
| Lifecycle | active | active |
| Released | 2025-10-15 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 200K | 33K |
| Total parameters | Unknown | 22.2B |
| Active parameters | Unknown | Unknown |
| License | Unknown | other |
| Open weights | No | Yes |
| API available | Yes | Unknown |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard), Deepinfra (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, tools | generation |
Claude Haiku 4.5 Capabilities
Codestral 22B v0.1 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Claude Haiku 4.5 vs Codestral 22B v0.1 FAQs
Is Claude Haiku 4.5 or Codestral 22B v0.1 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Haiku 4.5 and Codestral 22B v0.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Haiku 4.5 or Codestral 22B v0.1?+
Only Claude Haiku 4.5 has a directly sourced input price: $1.00 per million tokens. Only Claude Haiku 4.5 has a directly sourced output price: $5.00 per million tokens.
Which has a larger context window, Claude Haiku 4.5 or Codestral 22B v0.1?+
Claude Haiku 4.5 has the larger sourced context window. Claude Haiku 4.5 supports 200K and Codestral 22B v0.1 supports 33K.
Which performs better in benchmarks, Claude Haiku 4.5 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 Claude Haiku 4.5 or Codestral 22B v0.1 be self-hosted?+
Codestral 22B v0.1 is the only model in this pair currently marked as self-hostable. Claude Haiku 4.5 is not marked open weight; Codestral 22B v0.1 is open weight.
Can Claude Haiku 4.5 and Codestral 22B v0.1 understand images?+
Claude Haiku 4.5 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, Claude Haiku 4.5 or Codestral 22B v0.1?+
Neither has a larger sourced maximum output. Claude Haiku 4.5 is 64K and Codestral 22B v0.1 is —.
Do Claude Haiku 4.5 and Codestral 22B v0.1 support reasoning and tool use?+
Claude Haiku 4.5: 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, Claude Haiku 4.5 or Codestral 22B v0.1?+
Claude Haiku 4.5 has 2 sourced provider routes; Codestral 22B v0.1 has 0, so Claude Haiku 4.5 has broader tracked availability.
Which offers better value, Claude Haiku 4.5 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.