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Model profile
mistralai

Mistral Large 2411

Mistral Large 2411 is a mid-range-priced text-first model from mistralai with partial runtime data, extended context posture, and the clearest fit around long-context research.

Best for: Long-context researchN/A latencyExtended contextMid-range pricing
Agentic models
Intelligence
N/A

Benchmark blend

Coding
N/A

Dev workflow signal

Context
131K Tokens

Extended

Input Price
$2.00

Mid-range tier

Decision snapshot
69

Mistral Large 2411 currently reads as a mid-range text-first option with extended context and a partially published runtime profile.

Overall profile
Strong all-rounder
Best for
Long-context research
Latency tier
N/A
Price tier
Mid-range
Source coverage
OpenRouter
Open compare hubSee leaderboard

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
N/A
N/A

General reasoning and benchmark headroom.

Unavailable
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
131K Tokens
76

How much prompt and task state can stay in view.

Competitive
Price
$2.00
62

$6.00 output / 1M

Competitive

Editorial Profile

Mistral Large 2411 in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Strong all-rounderCoding score N/AMath score N/A

Mistral Large 2 2411 is an update of [Mistral Large 2](/mistralai/mistral-large) released together with [Pixtral Large 2411](/mistralai/pixtral-large-2411) It provides a significant upgrade on the previous [Mistral Large 24.07](/mistralai/mistral-large-2407), with notable...

Identity

mistralai text-first profile

Positioning

Long-context research with extended context and partially published runtime.

Cost posture

Balanced spend profile. Easier to justify in mixed production and exploration workloads.

Strengths

  • Large context headroom supports repo-wide prompts and long research sessions.

Tradeoffs

  • Costs look manageable, but still deserve attention in always-on agents or batch jobs.

  • Latency data is incomplete, so interactive responsiveness is harder to rank confidently.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

Best fit

  • Long-context summarization, repo analysis, and policy or document review.

Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

No benchmark data is available for this model yet.

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
131K Tokens
Vision
Text-first
Modalities
text
Tokenizer
Mistral
Moderation
No
Supported Parameters
frequency_penaltymax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$2.00
Output
per 1M output tokens
$6.00
Blended
AA 3:1 mix
N/A

This model sits in a balanced spend range. It is easier to justify across both production and exploratory workflows.

OR Cache Read
$0.00

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.