Context Window

Compare

Ministral 8b Latest vs Qwen3 1p7b Fp8 Draft

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Mistral

Model

Ministral 8b Latest

Image inputTool calling

Context window

262K

262,144 tokens · ~197K words

Model page
Alibaba

Model

Qwen3 1p7b Fp8 Draft

Context window

262K

262,144 tokens · ~197K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

Ministral 8b Latest262K
Qwen3 1p7b Fp8 Draft262K

Same context window size for both models.

Token calculator →Memory savings →

Ministral 8b Latest and Qwen3 1p7b Fp8 Draft have identical context windows (262K tokens). Qwen3 1p7b Fp8 Draft is 33% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Qwen3 1p7b Fp8 Draft. Input tokens are 33% cheaper — critical when sending large retrieved contexts.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecMinistral 8b LatestQwen3 1p7b Fp8 Draft
Context window262,144 tokens (262K)262,144 tokens (262K)
Max output tokens262,144 tokens (262K)262,144 tokens (262K)
Speed tierFastFast
VisionYesNo
Function callingYesNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AN/A

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderMinistral 8b Latest inMinistral 8b Latest outQwen3 1p7b Fp8 Draft inQwen3 1p7b Fp8 Draft out
Fireworks——$0.100/M$0.100/M
Mistral$0.150/M$0.150/M——

Frequently asked questions

Qwen3 1p7b Fp8 Draft has a larger context window: 262K tokens vs 262K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Calculate your savingsLearn about Mem0

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model