Verified November 2026

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Qwen 3 8B vs Mistral Small

A straight cost comparison of Qwen 3 8B (Alibaba (Qwen)) and Mistral Small (Mistral AI), per 1,000,000 tokens, verified November 2026.

$0.05Qwen 3 8B input / 1M
$0.10Mistral Small input / 1M
43%Blended price gap
Qwen 3 8BCheaper blended

Rate-by-rate comparison

USD per 1M tokens · November 2026
MetricQwen 3 8BMistral SmallWinner
Input / 1M$0.05$0.10Qwen 3 8B
Cached input / 1M$0.005$0.01Qwen 3 8B
Cache write / 1M——Tie
Output / 1M$0.20$0.30Qwen 3 8B
Context window131,07232,000Qwen 3 8B
Batch APIYesYesTie
Long-context tierNoneNone—

For per-token metrics, the lower number wins. For context window and batch support, the higher or broader option wins. A dash means the provider does not publish that rate: a missing cache-write fee means writes are not billed per token, while a missing cached-input rate means cache hits bill at the full input rate.

Blended cost: 1M input + 250K output

ModelBlended costDifference
Qwen 3 8B$0.10Cheaper
Mistral Small$0.175+$0.075

Ten workloads, two bills

The same two models, priced across ten workloads that differ only in their input:output ratio. Nothing else changes — no retries, no system prompt, no middleware.

WorkloadQwen 3 8BMistral SmallWinner
Classification
100K reqs · 500 in / 10 out
$2.70$5.30Qwen 3 8B
Data extraction
10K reqs · 2K in / 200 out
$1.40$2.60Qwen 3 8B
Support chat
1K reqs · 4K in / 600 out
$0.32$0.58Qwen 3 8B
Code review
2K reqs · 8K in / 1.5K out
$1.40$2.50Qwen 3 8B
Summarisation
1K reqs · 20K in / 1K out
$1.20$2.30Qwen 3 8B
Agent loop
5K reqs · 12K in / 2K out
$5$9Qwen 3 8B
Translation
500 reqs · 15K in / 15K out
$1.88$3Qwen 3 8B
Long-document QA
200 reqs · 120K in / 800 out
$1.23$2.45Qwen 3 8B
Cached RAG
1K reqs · 50K in (45K cached) / 1K out
$0.677$1.25Qwen 3 8B
Nightly batch
10K reqs · 10K in / 2K out
$4.50$8Qwen 3 8B

Qwen 3 8B wins 10 of 10, Mistral Small wins 0 of 10. The winner is set by the token mix, not by the headline rate.

Where the two bills cross over

Qwen 3 8B is cheaper on both sides of the mix: $0.05 vs $0.10 per million input tokens, and $0.20 vs $0.30 per million output. No input:output ratio reverses that, so on price alone the other model never becomes the better choice — it has to win on context, latency or output quality.

Cost at four scales

The same support-chat workload (4K input, 600 output per request) at four monthly volumes.

Requests / monthQwen 3 8BMistral SmallDifference
100$0.032$0.058Qwen 3 8B cheaper by $0.026
1,000$0.32$0.58Qwen 3 8B cheaper by $0.26
10,000$3.20$5.80Qwen 3 8B cheaper by $2.60
100,000$32$58Qwen 3 8B cheaper by $26

What caching does to each bill

Caching only helps the part of the prompt that repeats. This is the support-chat workload (1,000 requests, 4,000 input tokens each) with an increasing share of that prompt served from a warm cache, written once on the first request.

Cached share of the promptQwen 3 8BMistral SmallWinner
0%$0.32$0.58Qwen 3 8B
50%$0.23$0.40Qwen 3 8B
80%$0.176$0.292Qwen 3 8B
95%$0.149$0.238Qwen 3 8B

Both models publish a cached-read rate, so the discount is comparable: Qwen 3 8B reads cache at $0.005 per million, Mistral Small at $0.01.

Which one should you pick?

Qwen 3 8B wins on classification, data extraction, support chat, code review, summarisation, agent loop, translation, long-document qa, cached rag, nightly batch, while Mistral Small wins on none of the ten workloads above.

Beyond price, the two differ on input rate ($0.05 vs $0.10); output rate ($0.20 vs $0.30); cached-input rate ($0.005 vs $0.01); context window (131,072 vs 32,000).

Batch mode is available on Qwen 3 8B and Mistral Small, which halves the nightly job. Both publish cached-input discounts, so a stable system prompt is worth caching on either.

FAQ

Is Qwen 3 8B cheaper than Mistral Small?

On a blended 1M-input-plus-250K-output workload, Qwen 3 8B is cheaper by 43% ($0.10 vs $0.175). The gap changes for cache-heavy prompts and for batch jobs, as the workload table shows.

Which handles longer prompts, Qwen 3 8B or Mistral Small?

Mistral Small has the larger context window (131,072 vs 32,000 tokens). Neither model publishes a long-context surcharge.

Do both models support prompt caching?

Qwen 3 8B bills cached reads at $0.005 per 1M; Mistral Small at $0.01.

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