Mistral · Model release
Data as of October 6, 2026 · How the score is built
Mistral Large 4
Decision readingMistral Large 4 scores 53.7 out of 100 and ranks #69 of 214. This profile shows 3 source-displayable benchmark rows. API pricing is $0.68 input and $2.09 output per million tokens, with cached input at $0.07.
Released Oct 6, 2026 — see all recent releases
Mistral Large 4 will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
53.7/100
field median 52#69 of 214 ranked models
Public
#69of 214
Verified —
Price
$0.68input / $2.09 output
input median $0.95cached $0.070 · blended $1.39
Speed
116tok/s
field median 98 tok/sFirst token 18.69 s
Context
1Mtokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Published rows are visible, but no category has enough eligible evidence for a comparative rank.
Validate before choosing
3 published rows leave some tracked benchmark slots empty.
Source-linked · 3 displayable benchmark rows
Follow model changesCategory score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%2 benchmarksVerified | Score pending | 2 benchmarks | Verified | |||
| CodingWeight 20%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
3 of 655 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic2/2 verified
- Coding1/1 verified
- ReasoningNot measured
- MultimodalNot measured
- KnowledgeNot measured
- MultilingualNot measured
- Inst. FollowingNot measured
- MathNot measured
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Vibe Code BenchVibe Code Bench v1.1 | Score78.40% | Versus best verified row Best verified: Gemini 4 Argon · 91.90% | Gap13.5 behind | WeightDisplay only | Benchmark exact |
Agentic2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Cybench | Score93.0% | Versus best verified row Best verified: Mistral Large 4 · 93.0% | GapBest verified | WeightDisplay only | Provider exact |
| Finance Agent v2 | Score54.7% | Versus best verified row Best verified: Gemini 4 Argon · 65.4% | Gap10.7 behind | WeightDisplay only | Benchmark exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 3 rowsWhat it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
Mistral Large 4 · 53.7 score · $1.39 blended per million tokens
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Base entry
Mistral Large 4 release history
Radar confirmed these at the source. Use Mistral Large 4 in your work? Explore Radar to follow supported changes and choose your alerts.
Radar
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not publishedMistral AI Mistral Large 4 model documentation
- Context window
- 1MMistral AI Mistral Large 4 model documentation
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Public preview through Mistral Studio; Mistral says the weights are due by the end of October 2026.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.070 per million cached input tokensMistral AI Mistral Large 4 model documentation
- Self-host
- Weight availability is pending
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Mistral Large 4 ranks #69 of 214 on the public leaderboard with a score of 53.69/100. It does not yet have enough sourced coverage for a verified position.
Mistral Large 4 has no verified publication yet for weight access. Its 1M context window is documented separately from that pending weight status. The profile records its reasoning mode as hybrid.
Public preview through Mistral Studio; Mistral says the weights are due by the end of October 2026.
Mistral announced a public preview on October 6, 2026, and scheduled the weights for month-end. Its post reports 93% on Cybench. The refreshed Vals boards report 78.403 on Vibe Code Bench v1.1 and 54.678 on Finance Agent v2. Those display results do not enter the weighted ranking basket.
Its explicit predecessor is Mistral Large 3. 3 of 655 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Last updated October 6, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does Mistral Large 4 perform overall in AI benchmarks?
Mistral Large 4 ranks #69 out of 214 models on the public BenchAlign leaderboard, with a score of 53.69/100. Its evidence status is Estimated, and this profile shows 3 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Mistral Large 4 good for coding and programming?
Mistral Large 4 has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Mistral Large 4 good for agentic tool use and computer tasks?
Mistral Large 4 has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Does Mistral Large 4 have full benchmark coverage on BenchLM?
No. Mistral Large 4 currently has 18 source-displayable rows across 655 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Mistral Large 4?
Mistral Large 4 has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.