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NVIDIA: rerank-qa-mistral-4b

byNVIDIA

rerank-qa-mistral-4b is a reranking model from NVIDIA released on Mar 17, 2024. It reads text and writes relevance scores, with a 128K token context window.

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It costs $0 per million input tokens, with no charge for output.

Its weights are open, so you can host it yourself.

Modalities
In / out price
$0 / $0 per 1M
Context
128K
Max output
4K
Released
Mar 17, 2024
Knowledge cutoff
n/a
  • Tool calling
  • Structured output
  • Reasoning
  • Prompt caching
  • Open weights
  • Free to use

rerank-qa-mistral-4b pricing

USD, as listed on Oct 15, 2026. Most bills are input heavy, so the cached input rate matters as much as the headline price.

Input$0 / 1M tokens
Output$0 / 1M tokens

What rerank-qa-mistral-4b costs per month

Pick a workload close to yours or type your own volumes.

rerank-qa-mistral-4b per month
$0
Without caching
$0
Per request
$0

Alternatives to rerank-qa-mistral-4b

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  • Qwen3 Reranker 8B

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    by qwenJun 5, 2025$0.05/M input tokens

  • Qwen3 Reranker 4B

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    Reorders search results by relevance to a query.

    by qwenJul 30, 2025$0.0575/M input tokens

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All NVIDIA models

rerank-qa-mistral-4b questions

How much does the rerank-qa-mistral-4b API cost?

$0 per million input tokens and $0 per million output tokens. The estimator on this page turns that into a monthly bill for your own workload.

What is the context window of rerank-qa-mistral-4b?

128,000 tokens of input, and it can write up to 4,096 tokens in one reply. As a rough guide, a million tokens is around 750,000 English words.

Is rerank-qa-mistral-4b open source?

Its weights are published, so you can run it on your own hardware or a cloud of your choice. Read the license before commercial use.

When was rerank-qa-mistral-4b released?

Mar 17, 2024.

Catalog data from models.dev (MIT licensed), refreshed daily, last on Oct 15, 2026. The summary is written from these facts.

Building on rerank-qa-mistral-4b?

I test your real tasks on it and the two closest alternatives, then ship the agent on whichever wins on cost and accuracy.

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