Intelligence
4 scoreMistral · Flagships Analysis
Mistral Large (Feb)
Intelligence, Performance & Price Analysis
Canonical slug: mistral-large · Canonical model registry at build time
Input Price
$4.00 / 1M tokensOutput Price
$12.00 / 1M tokensExecutive Assessment
Routing Verdict & Tradeoffs
Ethen Routing Verdict
Budget-friendly / task-specific model
Mistral Large (Feb '24) scores 4 (estimated) on the Artificial Analysis Intelligence Index, placing it at the lower end among other non-reasoning models in a similar price tier (median: 17). Mistral Large (Feb '24) costs $4.00 per 1M input tokens (at the higher end, median: $1.88) and $12.00 per 1M output tokens (somewhat higher than average, median: $7.75), based on the median across providers serving the model.
Best for high-volume, simple, or domain-specific tasks where cost or speed matters more than deep reasoning.
Task Fit Assessment
| Workload | Rating | Notes |
|---|---|---|
| Complex reasoning & agentic workflows | suboptimal | Intelligence score 4 is better suited for straightforward tasks than multi-step reasoning. |
| Cost-sensitive pipelines | viable | Output pricing at $12.00 is premium. Route high-volume simple tasks to cheaper alternatives. |
Cost Pressure Analysis
High
Pricing is premium — input $4.00, output $12.00. This model is expensive for high-volume or output-heavy workloads.
Technical Specifications
Architecture and Limits
| Specification | Value | Validation Authority |
|---|---|---|
| Model type | Proprietary | inferred |
| Reasoning | No | faq |
| Input modalities | Mistral Large (Feb '24) supports text only input. | faq |
| Output modalities | Mistral Large (Feb '24) supports text only output. | faq |
| Context window | 33k tokens | faq |
| Open weights / source | No, Mistral Large (Feb '24) is proprietary. The model weights are not publicly available. | faq |
| Parameters | Mistral Large (Feb '24) is a proprietary model and Mistral has not disclosed the model size or parameter count. | faq |
| API availability | Yes, Mistral Large (Feb '24) 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.
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
Retrieved 2026-07-08
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.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
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
Retrieved 2026-07-08
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.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
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.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
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 should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
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.
Larger context windows enable complex multi-turn tasks but may increase latency and cost for long inputs.
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
Retrieved 2026-07-08
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.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
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.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
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
Retrieved 2026-07-08
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.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
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.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Methodology
Methodology & Provenance
This page is rendered from the normalized profile and page JSON for Mistral Large (Feb).
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.
Frequently Asked Questions
Model FAQs & Technical Disclosures
Mistral Large (Feb '24) was released on February 26, 2024.
Mistral Large (Feb '24) was created by Mistral.
Mistral Large (Feb '24) scores 4 (estimated) on the Artificial Analysis Intelligence Index, placing it at the lower end among other non-reasoning models in a similar price tier (median: 17).
Mistral Large (Feb '24) costs $4.00 per 1M input tokens (at the higher end, median: $1.88) and $12.00 per 1M output tokens (somewhat higher than average, median: $7.75), based on the median across providers serving the model.
Mistral Large (Feb '24) costs $4.00 per 1M input tokens and $12.00 per 1M output tokens (based on the median across providers serving the model). For a blended rate (7:2:1 cache hit/input/output ratio), this is $4.80 per 1M tokens. Pricing may vary by provider.
No, Mistral Large (Feb '24) is not a reasoning model. It provides direct responses without extended chain-of-thought reasoning.
Mistral Large (Feb '24) supports text only input.
Mistral Large (Feb '24) supports text only output.
No, Mistral Large (Feb '24) does not support image input. It can only process text.
No, Mistral Large (Feb '24) is not multimodal. It only supports text only input.
Mistral Large (Feb '24) has a context window of 33k tokens. This determines how much text and conversation history the model can process in a single request.
No, Mistral Large (Feb '24) is proprietary. The model weights are not publicly available.
Mistral Large (Feb '24) is a proprietary model and Mistral has not disclosed the model size or parameter count.
Mistral Large (Feb '24) achieves a score of 4 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Yes, Mistral Large (Feb '24) is available via API through 1 provider.
Mistral Large (Feb '24) is available through 1 API provider.