Granite 4.2 30B vs Mistral Large 3
Benchmark Performance
Available Benchmarks
| Benchmark | Granite 4.2 30B | Mistral Large 3 |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,362.5595% of row best · rating · granite-4.2-30b; 95% CI [1351.93384890, 1373.17607017]; votes 3287; rank 177 | 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 | Granite 4.2 30B | Mistral Large 3 |
|---|---|---|
| Developer | IBM | Mistral AI |
| Family | Granite 4 2 | Mistral Large 3 |
| Model | Granite 4.2 30B | Mistral Large 3 |
| Version | Granite 4.2 30B | Mistral Large 3 |
| Lifecycle | active | active |
| Released | 2026-08-25 | 2025-12-02 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image, Document |
| Output modalities | Text | Text |
| Context window | 131K | 262K |
| Total parameters | 29.3B | 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 | Deepinfra (Standard) | Mistral AI (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | agents, chat, generation, structured_outputs, tools, vision |
16 comparable fields · 11 material differences · Pair passes the primary-source comparison gate
Granite 4.2 30B Capabilities
Mistral Large 3 Capabilities
Internal Comparison Graph
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Primary Evidence
Sources and Freshness
Questions
Granite 4.2 30B vs Mistral Large 3 FAQs
Is Granite 4.2 30B or Mistral Large 3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Granite 4.2 30B and Mistral Large 3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Granite 4.2 30B or Mistral Large 3?+
Granite 4.2 30B is $0.16 and Mistral Large 3 is $0.50 per million tokens, so Granite 4.2 30B is cheaper on this metric. Granite 4.2 30B is $0.65 and Mistral Large 3 is $1.50 per million tokens, so Granite 4.2 30B is cheaper on this metric.
Which has a larger context window, Granite 4.2 30B or Mistral Large 3?+
Mistral Large 3 has the larger sourced context window. Granite 4.2 30B supports 131K and Mistral Large 3 supports 262K.
Which performs better in benchmarks, Granite 4.2 30B 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 Granite 4.2 30B or Mistral Large 3 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Granite 4.2 30B is open weight; Mistral Large 3 is open weight.
Can Granite 4.2 30B and Mistral Large 3 understand images?+
Granite 4.2 30B 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, Granite 4.2 30B or Mistral Large 3?+
Neither has a larger sourced maximum output. Granite 4.2 30B is — and Mistral Large 3 is —.
Do Granite 4.2 30B and Mistral Large 3 support reasoning and tool use?+
Granite 4.2 30B: reasoning and tool calling. Mistral Large 3: tool calling and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Granite 4.2 30B or Mistral Large 3?+
Granite 4.2 30B has 1 sourced provider route; Mistral Large 3 has 2, so Mistral Large 3 has broader tracked availability.
Which offers better value, Granite 4.2 30B 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.