Data as of October 19, 2026 · How the score is built
Released May 7, 2025128K context
Mistral Medium 3
Decision readingMistral Medium 3 scores 28.8 out of 100 and ranks #189 of 226. This profile shows 1 source-displayable benchmark rows. API pricing is $0.4 input and $2 output per million tokens.
Released May 7, 2025 — see all recent releases
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
28.8/100
field median 50#189 of 226 ranked models
Public
#189of 226
Verified —
Price
$0.40input / $2 output
input median $0.75blended $1.20
Speed
45tok/s
field median 94 tok/sFirst token 2.36 s
Context
128Ktokens
field median 256,000Reported for this model; direct source link not stored
Strongest published evidence
Published rows are visible, but no category has enough eligible evidence for a comparative rank.
Validate before choosing
1 published rows leave some tracked benchmark slots empty.
Source-linked · 1 displayable benchmark row
Category 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%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| 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 |
1 of 686 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.
- AgenticNot measured
- 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 |
|---|---|---|---|---|---|
| LiveCodeBench v6 | Score30.3% | Versus best verified row Best verified: Sakana Fugu-Ultra · 93.2% | Gap62.9 behind | WeightDisplay only | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 1 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 Medium 3 · 28.8 score · $1.20 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
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 published
- Context window
- 128K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not disclosed by the provider
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Established
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Weights are not published
- 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 Medium 3 ranks #189 of 226 on the public leaderboard with a score of 28.78/100. It does not yet have enough sourced coverage for a verified position.
Mistral Medium 3 is a proprietary model with a 128K context window. No explicit reasoning mode is documented in this profile.
1 of 686 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Last updated October 19, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does Mistral Medium 3 perform overall in AI benchmarks?
Mistral Medium 3 ranks #189 out of 226 models on the public BenchAlign leaderboard, with a score of 28.78/100. Its evidence status is Estimated, and this profile shows 1 source-displayable benchmark row. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Mistral Medium 3 good for coding and programming?
Mistral Medium 3 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.
Does Mistral Medium 3 have full benchmark coverage on BenchLM?
No. Mistral Medium 3 currently has 13 source-displayable rows across 686 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 Medium 3?
Mistral Medium 3 has a reported context window of 128K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.