Olmo 3 32B Think vs Mistral Large 3
Benchmark Performance
Available Benchmarks
| Benchmark | Olmo-3-32B-Think | Mistral Large 3 |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,299.5691% of row best · rating · olmo-3-32b-think; 95% CI [1291.25214421, 1307.87126458]; votes 5682; rank 230 | 1,427.62100% of row best · rating · mistral-large-3; 95% CI [1424.57601414, 1430.66670291]; votes 65336; rank 85 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark wins | 1 benchmark winOverall lead |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | Olmo-3-32B-Think | Mistral Large 3 |
|---|---|---|
| Developer | Ai2 | Mistral AI |
| Family | Olmo 3 32b Think | Mistral Large 3 |
| Model | Olmo-3-32B-Think | Mistral Large 3 |
| Version | Olmo-3-32B-Think | Mistral Large 3 |
| Lifecycle | active | active |
| Released | Unknown | 2025-12-02 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image, Document |
| Output modalities | Text | Text |
| Context window | 66K | 262K |
| Total parameters | 32.2B | 675B |
| Active parameters | Unknown | 41B |
| License | apache-2.0 | Apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Openrouter (Standard) | Mistral AI (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning | agents, chat, generation, structured_outputs, tools, vision |
15 comparable fields · 10 material differences · Pair passes the primary-source comparison gate
Olmo 3 32B Think Capabilities
Mistral Large 3 Capabilities
Internal Comparison Graph
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Primary Evidence
Sources and Freshness
Questions
Olmo 3 32B Think vs Mistral Large 3 FAQs
Is Olmo 3 32B Think or Mistral Large 3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Olmo 3 32B Think and Mistral Large 3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Olmo 3 32B Think or Mistral Large 3?+
Olmo 3 32B Think is $0.15 and Mistral Large 3 is $0.50 per million tokens, so Olmo 3 32B Think is cheaper on this metric. Olmo 3 32B Think is $0.50 and Mistral Large 3 is $1.50 per million tokens, so Olmo 3 32B Think is cheaper on this metric.
Which has a larger context window, Olmo 3 32B Think or Mistral Large 3?+
Mistral Large 3 has the larger sourced context window. Olmo 3 32B Think supports 66K and Mistral Large 3 supports 262K.
Which performs better in benchmarks, Olmo 3 32B Think or Mistral Large 3?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Olmo 3 32B Think or Mistral Large 3 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Olmo 3 32B Think is open weight; Mistral Large 3 is open weight.
Can Olmo 3 32B Think and Mistral Large 3 understand images?+
Olmo 3 32B Think is not documented with image input; Mistral Large 3 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Olmo 3 32B Think or Mistral Large 3?+
Neither has a larger sourced maximum output. Olmo 3 32B Think is 33K and Mistral Large 3 is —.
Do Olmo 3 32B Think and Mistral Large 3 support reasoning and tool use?+
Olmo 3 32B Think: reasoning. Mistral Large 3: tool calling and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Olmo 3 32B Think or Mistral Large 3?+
Olmo 3 32B Think has 1 sourced provider route; Mistral Large 3 has 2, so Mistral Large 3 has broader tracked availability.
Which offers better value, Olmo 3 32B Think or Mistral Large 3?+
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.