Mistral Small 4 119B 2603 vs GPT-5.2 Pro
At a Glance
| Compare |  Mistral Small 4 119B 2603Mistral AI |  GPT-5.2 ProOpenAI |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.15Openrouter ↗ · Aug 29, 2026 | $21.00Openai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.60Openrouter ↗ · Aug 29, 2026 | $168.00Openai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 1,049K | 400K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 3, 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 | Mistral-Small-4-119B-2603 | GPT-5.2 Pro |
|---|---|---|
| Developer | Mistral AI | OpenAI |
| Family | Mistral Small 4 119b 2603 | Gpt 5 2 |
| Model | Mistral-Small-4-119B-2603 | GPT-5.2 Pro |
| Version | Mistral-Small-4-119B-2603 | GPT-5.2 Pro |
| Lifecycle | active | active |
| Released | Unknown | 2025-12-11 |
| Knowledge cutoff | Unknown | 2025-08-31 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 400K |
| Total parameters | 119.4B | Unknown |
| Active parameters | 6.5B | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Openrouter (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, structured_outputs, tools |
Mistral Small 4 119B 2603 Capabilities
GPT-5.2 Pro Capabilities
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Primary Evidence
Sources and Freshness
Questions
Mistral Small 4 119B 2603 vs GPT-5.2 Pro FAQs
Is Mistral Small 4 119B 2603 or GPT-5.2 Pro better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Mistral Small 4 119B 2603 and GPT-5.2 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Mistral Small 4 119B 2603 or GPT-5.2 Pro?+
Mistral Small 4 119B 2603 is $0.15 and GPT-5.2 Pro is $21.00 per million tokens, so Mistral Small 4 119B 2603 is cheaper on this metric. Mistral Small 4 119B 2603 is $0.60 and GPT-5.2 Pro is $168.00 per million tokens, so Mistral Small 4 119B 2603 is cheaper on this metric.
Which has a larger context window, Mistral Small 4 119B 2603 or GPT-5.2 Pro?+
Mistral Small 4 119B 2603 has the larger sourced context window. Mistral Small 4 119B 2603 supports 1,049K and GPT-5.2 Pro supports 400K.
Which performs better in benchmarks, Mistral Small 4 119B 2603 or GPT-5.2 Pro?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Mistral Small 4 119B 2603 or GPT-5.2 Pro be self-hosted?+
Mistral Small 4 119B 2603 is the only model in this pair currently marked as self-hostable. Mistral Small 4 119B 2603 is open weight; GPT-5.2 Pro is not marked open weight.
Can Mistral Small 4 119B 2603 and GPT-5.2 Pro understand images?+
Mistral Small 4 119B 2603 is documented with image input; GPT-5.2 Pro is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Mistral Small 4 119B 2603 or GPT-5.2 Pro?+
Neither has a larger sourced maximum output. Mistral Small 4 119B 2603 is — and GPT-5.2 Pro is 128K.
Do Mistral Small 4 119B 2603 and GPT-5.2 Pro support reasoning and tool use?+
Mistral Small 4 119B 2603: reasoning, tool calling, and image input. GPT-5.2 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Mistral Small 4 119B 2603 or GPT-5.2 Pro?+
Mistral Small 4 119B 2603 has 1 sourced provider route; GPT-5.2 Pro has 2, so GPT-5.2 Pro has broader tracked availability.
Which offers better value, Mistral Small 4 119B 2603 or GPT-5.2 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.