Mistral Large 2 (Nov '24)

Mistral Large 2 (Nov '24)

Mistraltext

API Available

Specifications

Context Window

Input Price/1M

$2.00

Output Price/1M

$6.00

Parameters

Speed

39 tok/s

Latency (TTFT)

583ms

Benchmarks

Mistral Large 2 (Nov '24) results on the main AI model evaluation benchmarks. Higher scores indicate better performance.

Agentic

BenchmarkScoreMaximumMethodology
Terminal-Bench Hard6.0100.0

Coding

BenchmarkScoreMaximumMethodology
SciCode29.0100.0
LiveCodeBench29.0100.0Artificial Analysis official API
AA Coding Index13.8100.0Artificial Analysis official API

Knowledge

BenchmarkScoreMaximumMethodology
MMLU-Pro70.0100.0

Long Context

BenchmarkScoreMaximumMethodology
AA-LCR5.0100.0

Math

BenchmarkScoreMaximumMethodology
MATH-50071.4100.0Artificial Analysis official API
AIME 202514.0100.0Artificial Analysis official API
AA Math Index14.0100.0Artificial Analysis official API

overall

BenchmarkScoreMaximumMethodology
AA Intelligence Index15.1100.0Artificial Analysis official API

Reasoning

BenchmarkScoreMaximumMethodology
MMLU Pro68.3100.0Artificial Analysis official API
GPQA Diamond49.0100.0Artificial Analysis official API
IFBench31.0100.0
HLE4.0100.0

Tool Use

BenchmarkScoreMaximumMethodology
Tau²-Bench31.0100.0

Information

Release date
November 18, 2024
Tool Calling
❌ Not supported
Vision
❌ Not supported
Audio
❌ Not supported

Full Analysis: Mistral Large 2 (Nov '24)

What is Mistral Large 2 (Nov '24)?

Mistral Large 2 (Nov '24) is an AI model developed by Mistral, classified as a text model. It focuses on text processing and natural language generation. As a proprietary model, it is available via Mistral's cloud API.

Pricing & Costs in 2026

Mistral Large 2 (Nov '24) is usage-based, priced at $2/1M input tokens and $6/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The mid-range pricing balances quality and cost for most professional applications.

Benchmarks & Performance

Mistral Large 2 (Nov '24) was evaluated on 15 different benchmarks, covering categories like Agentic, Coding, Knowledge, Long Context, Math, overall, Reasoning, Tool Use. Results show moderate performance across available evaluations.

It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.

Recommended Use Cases

Mistral Large 2 (Nov '24) specializes in text, offering advanced capabilities for creating and processing text content.

Comparison with Alternatives

In the 2026 AI model ecosystem, Mistral Large 2 (Nov '24) competes directly with similarly capable models. Mistral competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.

For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.

Frequently Asked Questions

What is Mistral Large 2 (Nov '24)?

Mistral Large 2 (Nov '24) is an AI model developed by Mistral. It is a text model.

How much does Mistral Large 2 (Nov '24) cost?

Mistral Large 2 (Nov '24) costs $2/1M input tokens and $6/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.

How does Mistral Large 2 (Nov '24) compare with other models?

In available benchmarks, Mistral Large 2 (Nov '24) scored: Terminal-Bench Hard: 6/100, SciCode: 29/100, LiveCodeBench: 29/100. See the full table above for a detailed comparison.

Is Mistral Large 2 (Nov '24) open source?

No, Mistral Large 2 (Nov '24) is a proprietary model from Mistral. It is available via cloud API. For open source alternatives, check our open source model ranking.

What is Mistral Large 2 (Nov '24) best for?

Mistral Large 2 (Nov '24) excels at general-purpose language tasks.

Last updated: June 01, 2026 View methodology →