AI Models · Open-Source vs Paid

Mistral Large Paid vs Mistral Medium 3.5 (batch) Open

Mistral Large vs Mistral Medium 3.5 (batch) compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

Mistral LargePaidMistral AI
$2 /M input
$6 /M outputManaged API (no infra to run)
TypeProprietary
Context window128K tokens
MultimodalNo
Self-hostNo
Mistral Medium 3.5 (batch)OpenMistral AI
$0.75 /M input
$3.75 /M outputNo per-token fees if you self-host
TypeOpen-weight
Context window262K tokens
MultimodalYes
Self-hostYes
Choose Mistral Medium 3.5 (batch) if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Mistral Large if you want frontier capability through a managed API with zero infrastructure to run.

Mistral Large vs Mistral Medium 3.5 (batch) specs

SpecMistral LargeMistral Medium 3.5 (batch)Winner
MakerMistral AIMistral AI
TypeProprietaryOpen-weightMistral Medium 3.5 (batch)
Context window128K tokens262K tokensMistral Medium 3.5 (batch)
Input price$2/M$0.75/M · free self-hostMistral Medium 3.5 (batch)
Output price$6/M$3.75/M · free self-hostMistral Medium 3.5 (batch)
Vision / multimodalNoYesMistral Medium 3.5 (batch)
Tool / function callingYesYes= Tie
Self-hostableNo (API only)YesMistral Medium 3.5 (batch)
LicenseProprietaryApache 2.0Mistral Medium 3.5 (batch)

Price gap & when to choose each

1.6×cheaper per output token

Mistral Medium 3.5 (batch) is ~1.6× cheaper than Mistral Large on output tokens ($3.75 vs $6 per M tokens).

Choose Mistral Large if…
  • You want frontier performance through a managed API
  • You value reliability & ecosystem
  • You don't want to manage infrastructure
Choose Mistral Medium 3.5 (batch) if…
  • You want to self-host or run on your cloud
  • You need the longer 262K context window
  • You prioritize data privacy & control
  • You want the lowest operating costs
  • You are building open or reproducible AI

Feature comparison

CapabilityMistral LargeMistral Medium 3.5 (batch)
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Mistral Large vs Mistral Medium 3.5 (batch)

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

Mistral Medium 3.5 (batch) delivers 2.2× more intelligence per dollar.
Mistral Large
Mistral Medium 3.5 (batch)
Intelligence index
6.8
14.9
Math index
0
GPQA
47.2%
74.8%
MMLU-Pro
68.3%
Humanity's Last Exam
2.9%
13.8%
Long Context Reasoning
2%
69.3%
LiveCodeBench
26.7%
MATH-500
71.4%
AIME
9.3%
AIME 2025
0%
IFBench
31.6%
68.8%
τ²-Bench
33%
94.2%
Coding index
46.9
SciCode
40.2%
τ-Bench Banking
15.1%
Terminal-Bench
50.6%
Terminal-Bench Hard
33.3%
Speed
0 tok/s
142.2 tok/s
Latency
0s
0.74s
Intelligence per $
2.3
5

Benchmark data by Artificial Analysis.

How Mistral Large and Mistral Medium 3.5 (batch) score

🏆 Best value & openness: Mistral Medium 3.5 (batch) (4.6 vs 2.7 / 5)
CriterionMistral LargeMistral Medium 3.5 (batch)
Cost-efficiency4.04.0
Context window3.54.0
Openness1.55.0
Self-hosting1.05.0
Multimodality3.55.0

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

Mistral Large Paid

Mistral AI · Proprietary

This is Mistral AI's flagship model, Mistral Large 2 (version `mistral-large-2407`). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news

Mistral Medium 3.5 (batch) Open

Mistral AI · Open-weight

Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...

Other models in these families

These variants are tracked but not compared here — one page per family keeps the comparison readable.

Other variants tracked
Mistral Medium 3.5Mistral Small 4Mistral Small 4 (batch)Mistral Medium 3.1Mistral Medium 3.1 (batch)Mistral Large 3 2512Mistral Large 3 2512 (batch)Devstral 2 2512Mistral Medium 3Mistral Small 3.1 24BMistral Small 3.2 24BMistral LargeMistral Large 2407Mistral Small 3SabaMinistral 3 14B 2512Mixtral 8x22B InstructMinistral 3 8B 2512Ministral 3 8B 2512 (batch)Ministral 3 3B 2512UncensoredCodestral 2508Codestral 2508 (batch)Voxtral Small 24B 2507Mistral Nemo

Frequently asked questions

Is Mistral Medium 3.5 (batch) as good as Mistral Large?

Mistral Medium 3.5 (batch) is open-weight and competitive on many tasks, but Mistral Large may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.

Can I run Mistral Medium 3.5 (batch) locally?

Yes. Mistral Medium 3.5 (batch) has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Mistral Large is API-only and cannot be self-hosted.

How much cheaper is Mistral Medium 3.5 (batch)?

Mistral Medium 3.5 (batch) costs $3.75/M output vs $6/M for Mistral Large — roughly 2x cheaper via API, and free if you self-host.

Mistral Large vs Mistral Medium 3.5 (batch) — which should I pick in 2026?

Choose Mistral Medium 3.5 (batch) if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Mistral Large if you want frontier capability through a managed API with zero infrastructure to run.

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