Mistral Large 3 Intelligence, Performance & Price Analysis
Model summary
IntelligenceUpdated
Speed
Input Price
Output Price
Verbosity
Mistral Large 3 is below average in intelligence and somewhat expensive when comparing to other open weight non-reasoning models of similar size. It's also slower than average and very verbose. The model supports text and image input, outputs text, and has a 256k tokens context window.
Mistral Large 3 scores 16 on the Artificial Analysis Intelligence Index, placing it below average among comparable models (averaging 17). When evaluating the Intelligence Index, it generated 5.6M tokens, which is very verbose in comparison to the average of 5.2M.
Pricing for Mistral Large 3 is $0.50 per 1M input tokens (somewhat expensive, average: $0.40) and $1.50 per 1M output tokens (moderately priced, average: $1.50). In total, it cost $71.04 to evaluate Mistral Large 3 on the Intelligence Index.
At 49 tokens per second, Mistral Large 3 is slower than average (57).
| Reasoning | No This page shows the non-reasoning version of this model. A reasoning variant may also exist. |
|---|---|
| Input modality | Supports: text, image |
| Output modality | Supports: text |
| Context window | 256k ~384 A4 pages of size 12 Arial font |
| Total parameters | 675B |
| Active parameters | 41B Number of parameters active per token during inference |
| License | Apache 2.0 |
| Model weights | Hugging Face |
Metrics are compared against models of the same class:
- Non-reasoning models → compared only with other non-reasoning models
- Reasoning models → compared across both reasoning and non-reasoning
- Open weights models → compared only with other open weights models of the same size class:
- Tiny: ≤4B parameters
- Small: 4B–40B parameters
- Medium: 40B–150B parameters
- Large: >150B parameters
- Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:
- <$0.15 per 1M tokens
- $0.15–$1 per 1M tokens
- >$1 per 1M tokens
Highlights
IntelligenceUpdated
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Intelligence Evaluations
Agentic real-world work tasks, (Elo-500)/2000
Agentic tool use
Agentic coding & terminal use
Coding
Reasoning & knowledge
Scientific reasoning
Physics reasoning
Knowledge
1 - hallucination rate
Long context reasoning
Agentic knowledge work, (Elo-500)/2000
Instruction following
Long-horizon agentic tasks
Kubernetes incident root-cause analysis
Visual reasoning
AA-BriefcaseNew
AA-Briefcase Elo
Openness
Artificial Analysis Openness Index: Score
Intelligence Index Comparisons
Intelligence vs. Cost per Intelligence Index Task
Token UseUpdated
Output Tokens per Intelligence Index Task
Price and CostUpdated
Cost per Intelligence Index Task
Cost to Run Artificial Analysis Intelligence Index
Pricing: Cache Hit, Input, and Output
Context Window
Context Window
SpeedUpdated
Measured by Output Speed (tokens per second)
Output Speed
Time per Intelligence Index Task
Latency
Measured by Time (seconds) to First Token
Latency: Time To First Answer Token
End-to-End Response Time
Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed
End-to-End Response Time
Model Size (Open Weights Models Only)
Model Size: Total and Active Parameters
Frequently Asked Questions
Common questions about Mistral Large 3
Mistral Large 3 was released on December 2, 2025.
Mistral Large 3 was created by Mistral.
Mistral Large 3 scores 16 on the Artificial Analysis Intelligence Index, placing it below average among other open weight non-reasoning models of similar size (median: 17).
Mistral Large 3 generates output at 48.8 tokens per second (based on Mistral's API), which is below average compared to other open weight non-reasoning models of similar size (median: 56.6 t/s).
Mistral Large 3 has a time to first token (TTFT) of 1.20s (based on Mistral's API), which is very competitive compared to other open weight non-reasoning models of similar size (median: 2.54s).
Mistral Large 3 costs $0.50 per 1M input tokens (better than average, median: $0.56) and $1.50 per 1M output tokens (better than average, median: $1.90), based on Mistral's API.
Mistral Large 3 costs $0.50 per 1M input tokens and $1.50 per 1M output tokens (based on Mistral's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.60 per 1M tokens. Pricing may vary by provider. Compare provider pricing
When evaluated on the Intelligence Index, Mistral Large 3 generated 5.6M output tokens, which is better than average compared to other open weight non-reasoning models of similar size (median: 5.2M).
No, Mistral Large 3 is not a reasoning model. It provides direct responses without extended chain-of-thought reasoning.
Mistral Large 3 supports text and image input.
Mistral Large 3 supports text output.
Yes, Mistral Large 3 supports image input and can analyze, describe, and answer questions about images.
Yes, Mistral Large 3 is multimodal. It can process text and image input and generate text output.
Mistral Large 3 has a context window of 260k tokens. This determines how much text and conversation history the model can process in a single request.
Yes, Mistral Large 3 is open weights. The model weights are publicly available and can be downloaded for self-hosting.
Mistral Large 3 has 675 billion parameters (41 billion active).
Mistral Large 3 is a Mixture of Experts (MoE) model with 675 billion total parameters, but only 41 billion active parameters are used during inference.
Mistral Large 3 is released under the Apache 2.0 license. This license allows commercial use. View license
Mistral Large 3 achieves a score of 16 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Mistral Large 3 is an open weights model that can be self-hosted. View providers
Mistral Large 3 is an open weights model that can be downloaded and self-hosted. Compare providers