Intelligence
4
score
Mistral Large (Feb '24) scores 4 (estimated) on the Artificial Analysis Intelligence Index, placing …
vs class avg: 17
Mistral•Open weights•February 26, 2024
Mistral Large (Feb)
Intelligence, Performance & Price Analysis
Source:Artificial Analysis scrapeType:Open weights
Input Price#65/76
$4.00
/ 1M tokens
Mistral Large (Feb '24) costs $4.00 per 1M input tokens (at the higher end, median: $1.88) and $12. …
Output Price#53/76
$12.00
/ 1M tokens
Mistral Large (Feb '24) costs $4.00 per 1M input tokens (at the higher end, median: $1.88) and $12. …
Speed
not provided
This profile does not provide this metric.
Latency
not provided
This profile does not provide this metric.
Decision Overview
Ethen's intelligence-driven routing assessment for this model
Overall verdict
Budget-friendly / task-specific model
Best for high-volume, simple, or domain-specific tasks where cost or speed matters more than deep reasoning.
Best for
- Simple Q&A
- High-throughput chat
- Classification
- Extraction
- High-value tasks where quality outweighs cost
Weak or unsuitable
- Complex reasoning
- Creative writing
- Multi-step tasks
- Routine high-volume generation
- Simple extraction or labeling
Routing recommendation
1
Lower-cost models for repetitive or high-volume work
2
Cache-backed reuse for repeated prompts
Cost pressure
Premium pricing — $4.00 / M input, $12.00 / M output. Use cheaper routes for repetitive or low-risk work.
Model-fit matrix
Use this model where capability pays for itself; route away where volume, latency, or budget dominate.
| Use case | Fit | Reason | Routing note |
|---|---|---|---|
| Complex reasoning & agentic workflows | Weak | Intelligence score 4 is better suited for straightforward tasks than multi-step reasoning. | Avoid routing complex agentic tasks to this model. |
| Cost-sensitive pipelines | Moderate | Output pricing at $12.00 is premium. Route high-volume simple tasks to cheaper alternatives. | Use only for high-value tasks; route simple queries to budget models. |
Cost pressure
HighPricing is premium — input $4.00, output $12.00. This model is expensive for high-volume or output-heavy workloads.
Cheaper substitutes
- Lower-cost models for repetitive or high-volume work
- Cache-backed reuse for repeated prompts
Route away when
- Output-heavy tasks
- High-frequency chat at scale
- Simple queries that cheaper models handle well
Highlights
Key benchmark results at a glance.
Intelligence
Intelligence position
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
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).
Speed
Speed position
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Higher throughput supports faster interactive use.
Context, Cost & Pricing
Price/value position
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Pricing is premium — input $4.00, output $12.00. This model is expensive for high-volume or output-heavy workloads.
Intelligence & Quality
Benchmark scores and quality indices measuring model capability.
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
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
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
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
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
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Speed & Throughput
Output tokens per second and generation throughput.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Speed should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Context, Cost & Pricing
Context window size, cost per task, and token pricing.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
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
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
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
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
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
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
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
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Specifications
Technical Specifications
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)
- Model type
- Open weights
- Reasoning
- No
- Input modalities
- Mistral Large (Feb '24) supports text only input.
- Output modalities
- Mistral Large (Feb '24) supports text only output.
- Context window
- 33k tokens
- Open weights / source
- No, Mistral Large (Feb '24) is proprietary. The model weights are not publicly available.
- Parameters
- Mistral Large (Feb '24) is a proprietary model and Mistral has not disclosed the model size or parameter count.
- API availability
- Yes, Mistral Large (Feb '24) is available via API through 1 provider.
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.
Source file: md/scrape/artificial_analysis_model_pages/artificialanalysis_ai__models__mistral-large__7474dd51a5.html · Canonical URL: https://artificialanalysis.ai/models/mistral-large
Normalized at: 2026-07-08T03:24:56+00:00 Technical specs, comparison summary, and FAQs are passed through from the normalized data without rewriting.
Ranks shown on summary cards come directly from the normalized profile. No rank or class display is synthesized in the renderer.
Visible FAQ answers and FAQ JSON-LD are emitted from the same normalized FAQ array, so structured data stays aligned with the rendered accordion.
Speed: https://artificialanalysis.ai/models/mistral-large
Frequently Asked Questions
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).