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Specifications
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality.
—6B
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider.
32k2k
API pricingUSD per 1M tokens · lower wins
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page.
$2.00Mistral—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$6.00Mistral—
$700Mistral—
Overview
CompanyMistralZ.ai
Release dateFeb 26 2024Mar 14 2023
AccessClosedOpen Weight
Model detailsView modelView model

Other comparisons

Mistral LargevsClaude Haiku 5.5ChatGLM-6BvsClaude Haiku 5.5Mistral LargevsGPT-6.1 SolChatGLM-6BvsGPT-6.1 SolMistral LargevsGemini 4 ArgonChatGLM-6BvsGemini 4 ArgonMistral LargevsMuse Spark OpenChatGLM-6BvsMuse Spark OpenMistral LargevsGrok 4.7ChatGLM-6BvsGrok 4.7Mistral LargevsDeepSeek-V4.1-Flash-1017ChatGLM-6BvsDeepSeek-V4.1-Flash-1017

Frequently asked questions

Mistral Large and ChatGLM-6B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. ChatGLM-6B shipped 349 days before Mistral Large, so benchmark comparisons should account for the intervening progress.

Context windows are 32k (Mistral Large) vs 2k (ChatGLM-6B). Mistral Large is closed, while ChatGLM-6B is open weight.

Direct benchmark comparisons are unavailable — Mistral Large and ChatGLM-6B don't publish scores on any of the same benchmarks.