Mistral

Mistral Nemo

mistralai/mistral-nemo
Model weightsReleased Jul 19, 2024Open Weights
Toolsopen weights

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

Cost / 1M tokens

Very low usage

$0.029

input

—

cached input

$0.03

output

Context Window

131K

Up to 16K max output

Modalities

text → text

Mistral tokenizer

Quickstart & API

mistralai/mistral-nemo
Open the model picker in ChatOSS Desktop (Code, Kanban, or Chat) and select or paste this model ID.

Best for & Strengths

Key Strengths

Open weightsTool & agent calling

Recommended Workloads in ChatOSS

  • Coding agents
  • Open-source AI workflows
Available in ChatOSS Code, Kanban Orchestrate, and Chat modes via Plus, Max, or BYOK.

Active Provider Endpoints (5)

Upstream inference providers serving Mistral Nemo, with per-provider pricing, context limits, quantization, and 24-hour uptime.

ProviderInput / 1MOutput / 1MCache Read / 1MContextMax OutputQuantizationUptime (24h)
Io Netcache
io-net/fp16
$0.017$0.022$0.011128K102Kfp1699.9%
DekaLLM
dekallm/fp8
$0.018$0.03—131K105Kfp899.8%
DeepInfra
deepinfra/fp8
$0.029$0.03—131K16Kfp8100.0%
Parasail
parasail/fp8
$0.03$0.03—131K105Kfp899.4%
Mistralcache
mistral/eu
$0.15$0.15$0.015131K105K—100.0%

Supported API Parameters

Parameters accepted by this model when called through ChatOSS or OpenRouter.

frequency_penaltylogit_biaslogprobsmax_tokensmin_ppresence_penaltyrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p

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