Mistral Large 3
Mistral Large 3 is Mistral's open-weight, general-purpose multimodal model, released under Apache 2.0 for chat, document question-answering, and agentic workloads.
input · usd / 1m tok
$0.50
output · usd / 1m tok
$1.50
context window
128ktokens
modalities · in → out
takes text and image in, gives text out
pricing
base api ratesusd per 1m tokens
- input
- $0.50
- output
- $1.50
providers
Azure AI Foundry hosts Mistral Large 3. Impossibl routes your request intelligently and handles failover automatically when a provider is down.
- Azure AI Foundry
specifications
takes text and image in, gives text outmistral/mistral-large-3
- creatorMistral
- model typeText generation
- context window128,000 tokens
- maximum outputnot published
- input
takes text and image in, gives text out
- outputtext
- tool callingnot verified
- releaseddec 2, 2025
- endpoint
/v1/chat/completions
unknown means the public catalog does not establish that fact. a model's documented capabilities can differ from what a particular api supports. see the model documentation for integration details.
try it · your prompt, this model, live
# responses API
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["IMPOSSIBL_API_KEY"],
base_url="https://api.impossibl.com/v1",
)
resp = client.responses.create(
model="mistral/mistral-large-3",
input="",
)
print(resp.output_text)
edit the prompt, then run
benchmarks
intelligence index
9.7#81 of 90 models on the gateway
- coding index20.1#55 of 60
- agentic index2.4#48 of 49
- omniscience-39.6#73 of 86
- gpqa68.0%#76 of 88
- humanity’s last exam4.2%#83 of 89
- terminal-bench v2.112.0%#52 of 57
- GPQA68.0%
- MMMU-Pro55.7%
- LiveCodeBench46.5%
- AIME 202538.0%
- SciCode36.6%
- IFBench36.2%
- AA-LCR36.0%
- Tau224.6%
- Terminal-Bench Hard15.9%
- Terminal-Bench v2.112.0%
- Tau Banking5.8%
- Humanity’s Last Exam4.2%
- AutomationBench Partial1.5%
- GDP.pdf All-pass1.2%
- CritPt0.0%
- Terminal-Bench v4.00.0%
- Intelligence Index9.71
- Omniscience Index-39.57
- GDPval Elo588.39
- coding index (API)20.1
- agentic index (API)2.4
- intelligence index (API)9.7
each configuration is listed separately; these evaluations describe the tested model configuration, and performance and costs can differ on impossibl. unmeasured scores are omitted and api values keep their source units. last checked 2026-09-11.
compare Mistral Large 3 with other models
frontier labs and open weights, best-ranked firstusd / 1m tok · in / out
- anthropic/claude-fable-5-1$10.00 / $50.00compare →
- openai/gpt-6-astra$10.00 / $50.00compare →
- meta/muse-spark-1.3$1.25 / $4.25compare →
- zai/glm-5.3$1.40 / $4.40compare →
frequently asked questions
What is Mistral Large 3?
Mistral Large 3 is Mistral's open-weight, general-purpose multimodal model, released under Apache 2.0 for chat, document question-answering, and agentic workloads. It uses a granular mixture-of-experts design and supports function calling, structured outputs, built-in agent tools, and batch processing.
How much does Mistral Large 3 cost?
Mistral Large 3 costs $0.50 per million input tokens and $1.50 per million output tokens through the Impossibl API. All rates are in USD.
What is the context length of Mistral Large 3?
Mistral Large 3 has a 128,000-token context window through the Impossibl API.
What inputs and outputs does Mistral Large 3 support?
Mistral Large 3 accepts text and image as input. Mistral Large 3 returns text.
How do I use Mistral Large 3 through an API?
Mistral Large 3 is available through the Impossibl API. Use mistral/mistral-large-3 as the model identifier with /v1/chat/completions. The quickstart explains how to create an API key and send your first request.
When was Mistral Large 3 released?
Mistral released Mistral Large 3 on December 2, 2025.
this page describes Mistral Large 3 as listed by the impossibl public api. prices and availability come from that catalog, refreshed here every five minutes. this is an impossibl offering, not a comparison of independent hosting-provider quotes. model descriptions and release dates, where available, use the creator sources linked under the answers above.
view the source catalog ↗model as markdown ↗report a correction →