Mistral Large 4
MistralKey mistral-large-4Also reported as mistral/mistral-large-4, mm0e-com/commandcode/mistral/mistral-large-4
- Rank
- #149
- by active users
- Active users
- 2
- NewNew: no active users in the previous 7 days, 2 now. vs previous 7 days
- Adoption
- 0.3%
- of 598 accounts
- Tokens
- 5K
- cache included
- Est. cost
- <$1
- at public list prices
- First seen
- Oct 7, 2026
- in any submission
Nov 7–13, 2026 (UTC)598 accounts100% of tokens from an identified modelData through Nov 13, 2026, 01:19 UTCHow we count
Daily active users
Distinct accounts that used this model on each UTC day.
0 active users on Nov 13, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Nov 7, 2026 | 0 | 0 |
| Nov 8, 2026 | 0 | 0 |
| Nov 9, 2026 | 1 | 4.9K |
| Nov 10, 2026 | 0 | 0 |
| Nov 11, 2026 | 1 | 72 |
| Nov 12, 2026 | 0 | 0 |
| Nov 13, 2026 | 0 | 0 |
Token mix
How the 5K tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input43%
- Output12%
- Cache read0%
- Cache write0%
- Reasoning44%
Agents that carry Mistral Large 4
Each agent's share of this model's tokens, and how many accounts used the model through it.
Pi99% of this model's tokens1active users
Senpi (OmO Native)1.5% of this model's tokens1active users
Benchmarks
The best result for Mistral Large 4 in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark.
- Epoch Capabilities IndexOverall · Epoch AI154.6
Epoch Capabilities Index: 154.6
- Model
- Mistral Large 4
- Listed as
- Mistral Large 4
- Conditions
- Not reported
- Interval
- 151.8–157.5
- Unit
- ECI
- Model released
- Oct 29, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #48 of 158 matched modelsNo conditions reportedModel released Oct 29, 2026Source: epoch.ai (opens in a new tab) - WebDev ArenaWeb development · LMArena1,543
WebDev Arena: 1,543
- Model
- Mistral Large 4
- Listed as
- Mistral Large 4
- Conditions
- Not reported
- Interval
- 1530–1555
- Unit
- Arena score
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #40 of 110 matched modelsNo conditions reportedPublished Oct 19, 2026Source: huggingface.co (opens in a new tab) - Agent ArenaAgents · LMArena−0.04
Agent Arena: −0.04
- Model
- Mistral Large 4
- Listed as
- Mistral Large 4
- Conditions
- Arena Agent Mode
- Interval
- -0.06 to -0.03
- Unit
- net improvement
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #38 of 48 matched modelsArena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab) - GPQA DiamondReasoning · Epoch AI90.2%
GPQA Diamond: 90.2%
- Model
- Mistral Large 4
- Listed as
- mistral-large-4-0-oss_high
- Conditions
- High
- Unit
- % correct
- Run date
- Nov 2, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.
- SimpleQA VerifiedKnowledge · Epoch AI22.4%
SimpleQA Verified: 22.4%
- Model
- Mistral Large 4
- Listed as
- mistral-large-4-0-oss_high
- Conditions
- High
- Unit
- % correct
- Run date
- Nov 2, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Pricing
List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. Mistral is the lab's own API and the reference price for the estimates below.
Price at real agent usageEstimate at list prices
What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.
- At this model's mix
- $1.49
- Est. per 1M tokens
0% cache reads - At the community mix
- $0.10
- Est. per 1M tokens
96% cache reads - 3:1 input/output blend
- $1.05
- Per 1M tokens at list prices
No cache
Cache reads were 0% of Mistral Large 4 tokens in the last 7 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.
Assumptions
- Mistral list prices per 1M tokens: input $0.70, output $2.10, cache read $0.07.
- This model's mix is its own input, output, cache and reasoning tokens in the last 7 days.
- The community mix is the tokens of every identified model in the last 7 days.
- This is an estimate at list prices, not what anyone paid.
- Reasoning tokens are priced as output.
- Long-context tiers, batch pricing and discounts are not applied.
- Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
- No cache-write price is listed, so cache writes are priced as input.
List prices by provider
- MistralReference
mistral-large-4$0.70 input per 1M tokens$2.10 output per 1M tokens$0.07 cache read per 1M tokensCache write not listed1.05M tokens of context - OpenRouter
mistralai/mistral-large-4-0$0.70 input per 1M tokens$2.10 output per 1M tokens$0.07 cache read per 1M tokensCache write not listed1.05M tokens of context - Vercel AI Gateway
mistral/mistral-large-4$0.70 input per 1M tokens$2.10 output per 1M tokens$0.07 cache read per 1M tokensCache write not listed1.05M tokens of context
Specs
From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.
- Context window
- 1.05M tokens
- Max output
- 262K tokens
- Input
- Text, Image, PDF
- Output
- Text
- Knowledge cutoff
- — not listed
- Release date
- Oct 6, 2026
- Open weights
- No
- Reasoning
- Yes
- Tool calling
- Yes
Top public profiles
Public profiles that used Mistral Large 4 most in this period, by tokens. Hidden accounts are never listed.
More from Mistral
Other Mistral models in the same period, by active users.
- Mistral Large Latest0.2% adoption1active users
- Mistral Medium 3 50.2% adoption1active users
Sources and attribution
Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.