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AI Choice Engine

Model comparison

Mistral Large 3 vs Mistral Medium 3.5

Two Mistral tiers compared on the figures that decide which one a workload actually needs.

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Mistral

Mistral Large 3

Frontier · Open weights

vs

Mistral

Mistral Medium 3.5

Frontier · Open weights

AI model capability comparison
SpecificationMistral Large 3Mistral Medium 3.5
ProviderMistralMistral
TierFrontierFrontier
Context window262K262K
Max outputNot verifiedUnverifiedNot verifiedUnverified
Input / 1M tokensWinner: $0.50$1.50
Output / 1M tokensWinner: $1.50$7.50
WeightsOpenOpen
Parameters675B total / 41B active (sparse MoE)128B dense
Reasoning levelsNot verifiedUnverifiedNot verifiedUnverified
Modalitiestext, imagetext, image
LicenseApache 2.0Modified MIT
API model idmistral-large-2512mistral-medium-3-5
ReleasedDecember 2, 2025April 28, 2026
Artificial Analysis Intelligence Index (2026-09-26)9.3Winner: 14.2
GPQA Diamond (2026-09-26)68Not verifiedUnverified

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

  • 2026-09-26
    Artificial Analysis GPQA Diamond (independent; replaces Mistral's non-comparable base-model 5-shot 43.9)

    Graduate-level science reasoning: multiple-choice questions written by domain PhDs.

    Comparable with caveatSmall question pool: differences under ~2 points are within run-to-run noise. Chain-of-thought vs direct answering must match to compare. Saturated: frontier models score ~93–96% and Artificial Analysis dropped it from its Intelligence Index in v4.3 — use Humanity's Last Exam for hard reasoning.

  • 2026-09-26
    Artificial Analysis

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.

Pricing tiers

Mistral Large 3: Mistral first-party API $0.50/$1.50 per MTok; cached input $0.05/MTok. Open weights (Apache 2.0), EU-hosted.

Mistral Medium 3.5: Mistral first-party API $1.50/$7.50 per MTok; Mistral advertises up to 90% off cached input (exact cached rate not verified). Open weights under a Modified MIT licence. 128B dense.

FrontierOpen weightsRecord checked September 26, 2026

Mistral Large 3

Mistral Large 3 is Mistral's December 2025 open-weight (Apache 2.0) 675B/41B sparse MoE with a 262K context at $0.50/$1.50 — Mistral now features Medium 3.5 as its flagship.

Best for

  • Open-weight deployments
  • Multimodal EU-hosted inference
  • Balanced frontier work

Watch out

No longer Mistral's featured flagship (Medium 3.5 is) and far behind it on the Artificial Analysis index; max output is not published. Verify multimodal support and EU data residency on your endpoint.

FrontierOpen weightsRecord checked September 26, 2026

Mistral Medium 3.5

Mistral Medium 3.5 is the model Mistral calls its new flagship — a 128B dense open-weight model with a 256K context, powering its Vibe remote agents.

Best for

  • EU-hosted frontier work
  • Open-weight self-hosting
  • Mistral Vibe agents

Watch out

Far behind US and Chinese frontier models on the Artificial Analysis index; max output is not published. Check the Modified MIT terms before redistribution.

When the cheaper one wins

Mistral Large 3 is cheaper on output at $1.50 per million tokens against $7.50 for Mistral Medium 3.5 — about 5.0×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

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Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

  • Pricing verified on both sides — Input and output rates are verified for both models.
  • 3/5 core specs verified on both sides — Not published for at least one side: max output, reasoning levels.
  • 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
  • Verified within the last 90 days — Newest catalog check was 2 days ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? Mistral Large 3 · Mistral Medium 3.5

Common questions

Mistral Large 3 vs Mistral Medium 3.5

Answered from the verified figures on this page rather than general guidance.

Is Mistral Large 3 or Mistral Medium 3.5 cheaper for input?
Mistral Large 3 is cheaper at $0.50 per million input tokens, against $1.50 for Mistral Medium 3.5 — roughly 3.0× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Mistral Large 3 has tiered pricing: Mistral first-party API $0.50/$1.50 per MTok; cached input $0.05/MTok. Open weights (Apache 2.0), EU-hosted. Mistral Medium 3.5 has tiered pricing: Mistral first-party API $1.50/$7.50 per MTok; Mistral advertises up to 90% off cached input (exact cached rate not verified). Open weights under a Modified MIT licence. 128B dense.
Is Mistral Large 3 or Mistral Medium 3.5 cheaper for output?
Mistral Large 3 is cheaper at $1.50 per million output tokens, against $7.50 for Mistral Medium 3.5 — roughly 5.0× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Mistral Large 3 has tiered pricing: Mistral first-party API $0.50/$1.50 per MTok; cached input $0.05/MTok. Open weights (Apache 2.0), EU-hosted. Mistral Medium 3.5 has tiered pricing: Mistral first-party API $1.50/$7.50 per MTok; Mistral advertises up to 90% off cached input (exact cached rate not verified). Open weights under a Modified MIT licence. 128B dense.
Which has the larger context window, Mistral Large 3 or Mistral Medium 3.5?
Both accept about 262K tokens of context, so document length will not decide between them.
Should I use Mistral Large 3 or Mistral Medium 3.5?
Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. Mistral Large 3 suits open-weight deployments; Mistral Medium 3.5 suits eu-hosted frontier work.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Input price: Mistral Large 3 costs $0.50 per 1M tokens versus $1.50 for Mistral Medium 3.5 — a 3x difference at the headline tier.
  • Measured capability: Mistral Medium 3.5 leads Artificial Analysis Intelligence Index 14.2 to 9.3 (measured 2026-09-26).
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