mistral-large-3-fp8

fireworks_ai · Chat model

mistral-large-3-fp8 is listed here as a chat model from fireworks_ai. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Provider and model identifiers are kept in their original form for accuracy.

fireworks_ai-fireworks_ai-accounts-fireworks-models-mistral-large-3-fp8

Input

$1.2000 / 1M tokens

Output

$1.2000 / 1M tokens

Cached input

N/A

Context window

256.0K

Catalog generated: Jul 13, 2026

Compare this model Open a side-by-side table using this route and a close match from the current catalog. Estimate cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill.

Quick read

Best for

Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.

Things to verify

Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.

Pricing

Item	Price
Input	$1.2000 / 1M tokens
Output	$1.2000 / 1M tokens
Embedding	$1.2000 / 1M tokens

Limits

Context window

256.0K

Max input tokens

256.0K

Max output tokens

256.0K

Max tokens

256.0K

Explore benchmark family Review source-backed benchmark rows for the attached base model family. Check data sources See how pricing data is generated and what still needs provider verification. API vs subscription Learn when API pricing matters compared with ChatGPT, Claude Code, Cursor, or Copilot subscriptions. Cache and batch pricing Understand cached input, cache write, batch, priority, and flex pricing rows shown on this page.

Capabilities

Capability	Supported
Vision	-
Function calling	-
Parallel function calling	-
Tool choice	-
Prompt caching	-
Reasoning	-
Response schema	-
System messages	-
Audio input	-
Audio output	-
Web search	-
PDF input	-
Video input	-

Benchmarks

Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer

Benchmark	Score	Metric	Scope	Checked	Source
MMLU	85.5	accuracy	Base model: mistral-large-3 (Mistral Large 3)	2026-05-31	Link
MMLU-Pro	78.0	accuracy	Base model: mistral-large-3 (Mistral Large 3)	2026-05-31	Link
GPQA Diamond	43.9	accuracy	Base model: mistral-large-3 (Mistral Large 3)	2026-05-31	Link
HumanEval	92.0	pass@1	Base model: mistral-large-3 (Mistral Large 3)	2026-05-31	Link
MATH-500	93.6	accuracy	Base model: mistral-large-3 (Mistral Large 3)	2026-05-31	Link
AIME 2024	53.3	accuracy	Base model: mistral-large-3 (Mistral Large 3)	2026-05-31	Link
AIME 2025	40.0	accuracy	Base model: mistral-large-3 (Mistral Large 3)	2026-05-31	Link
SimpleQA	23.8	accuracy	Base model: mistral-large-3 (Mistral Large 3)	2026-05-31	Link

Sources

Source links	LiteLLM repository LiteLLM model cost map
Pricing data	LiteLLM model cost map
Synced at	2026-05-28
Catalog generated	2026-07-13T14:21:55.110Z