Intelligence
30 scoreMistral · Flagships Analysis
Mistral Medium 3.5
Intelligence, Performance & Price Analysis
Canonical slug: mistral-medium-3-5 · Canonical model registry at build time
Speed
140.3 output tokens/secLatency
2.02s TTFTInput Price
$1.50 / 1M tokensOutput Price
$7.50 / 1M tokensVerbosity
91M Output tokens from Intelligence Index 3 out of 4 units for Verbosity . CompaExecutive Assessment
Routing Verdict & Tradeoffs
Frontier research / complex reasoning
Mistral Medium 3.5 scores 30 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 9). Mistral Medium 3.5 generates output at 140.3 tokens per second (based on Mistral's API), which is above average compared to other open weight models of similar size (median: 88.2 t/s). Mistral Medium 3.5 costs $1.50 per 1M input tokens (at the higher end, median: $0.40) and $7.50 per 1M output tokens (at the higher end, median: $0.84), based on Mistral's API.
Reserve this model for the hardest requests; simpler or repetitive work should stay on cheaper routes.
Task Fit Assessment
| Workload | Rating | Notes |
|---|---|---|
| Complex reasoning & agentic workflows | optimal | Intelligence score 30 places this model among top performers. Suitable for multi-step analysis and agentic loops. |
| High-volume chat & customer-facing | optimal | Output speed 140.3 tokens/sec and capable intelligence make this suitable for real-time chat at scale. |
| Latency-sensitive applications | optimal | TTFT 2.02s — adequate latency for most interactive use cases. |
| Cost-sensitive pipelines | viable | Output pricing at $7.50 is premium. Route high-volume simple tasks to cheaper alternatives. |
Cost Pressure Analysis
High
Pricing is premium — input $1.50, output $7.50. This model is expensive for high-volume or output-heavy workloads.
Technical Specifications
Architecture and Limits
| Specification | Value | Validation Authority |
|---|---|---|
| Model type | Open weights | inferred |
| Reasoning | Yes | faq |
| Input modalities | Mistral Medium 3.5 supports text and image input. | faq |
| Output modalities | Mistral Medium 3.5 supports text output. | faq |
| Context window | 260k tokens | faq |
| Open weights / source | Yes, Mistral Medium 3.5 is open weights. The model weights are publicly available and can be downloaded for self-hosting. | faq |
| Parameters | Mistral Medium 3.5 has 128 billion parameters. | faq |
| License | Mistral Medium 3.5 is released under the Other license. This license allows commercial use. | faq |
| API availability | Yes, Mistral Medium 3.5 is available via API through 1 provider. | faq |
Evidence charts
Profile visualizations
Charts are the same canonical evidence cards previously published for this slug, contained inside the D18D page grammar.
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Artificial Analysis Openness Index: Score
Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open) · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Output Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
End-to-End Response Time
Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Latency: Time To First Answer Token
Seconds to first answer token received · Accounts for reasoning model 'thinking' time · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Time per Intelligence Index Task
Weighted average decode time (minutes) per task; excludes TTFT and overhead time · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Model Size: Total and Active Parameters
Comparison between total model parameters and parameters active during inference · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Output Tokens per Intelligence Index Task
Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Methodology
Methodology & Provenance
This page is rendered from the normalized profile and page JSON for Mistral Medium 3.5.
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.
Frequently Asked Questions
Model FAQs & Technical Disclosures
Mistral Medium 3.5 was released on April 29, 2026.
Mistral Medium 3.5 was created by Mistral.
Mistral Medium 3.5 scores 30 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 9).
Mistral Medium 3.5 generates output at 140.3 tokens per second (based on Mistral's API), which is above average compared to other open weight models of similar size (median: 88.2 t/s).
Mistral Medium 3.5 has a time to first token (TTFT) of 2.02s (based on Mistral's API), which is somewhat higher than average compared to other open weight models of similar size (median: 1.52s).
Mistral Medium 3.5 costs $1.50 per 1M input tokens (at the higher end, median: $0.40) and $7.50 per 1M output tokens (at the higher end, median: $0.84), based on Mistral's API.
Mistral Medium 3.5 costs $1.50 per 1M input tokens and $7.50 per 1M output tokens (based on Mistral's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $1.16 per 1M tokens. Pricing may vary by provider.
When evaluated on the Intelligence Index, Mistral Medium 3.5 generated 91M output tokens, which is somewhat higher than average compared to other open weight models of similar size (median: 59M).
Yes, Mistral Medium 3.5 is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
Mistral Medium 3.5 supports text and image input.
Mistral Medium 3.5 supports text output.
Yes, Mistral Medium 3.5 supports image input and can analyze, describe, and answer questions about images.
Yes, Mistral Medium 3.5 is multimodal. It can process text and image input and generate text output.
Mistral Medium 3.5 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 Medium 3.5 is open weights. The model weights are publicly available and can be downloaded for self-hosting.
Mistral Medium 3.5 has 128 billion parameters.
Mistral Medium 3.5 is released under the Other license. This license allows commercial use.
Mistral Medium 3.5 achieves a score of 30 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Yes, Mistral Medium 3.5 is available via API through 1 provider.
Mistral Medium 3.5 is available through 1 API provider.