Model comparison

Mistral Small 4 vs Qwen 3.8 27B

Mistral against Qwen, compared on context, price, and verified benchmark results.

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Mistral

Mistral Small 4

Budget · Open weights

Qwen

Qwen 3.8 27B

Budget · Open weights

AI model capability comparison
Specification	Mistral Small 4	Qwen 3.8 27B
Provider
Provider	Mistral	Qwen
Tier
Tier	Budget	Budget
Context window
Context window	262K	262K
Max output
Max output	Not verifiedUnverified	Not verifiedUnverified
Input / 1M tokens
Input / 1M tokens	Winner: $0.15	$0.50
Output / 1M tokens
Output / 1M tokens	Winner: $0.60	$3
Weights
Weights	Open	Open
Parameters
Parameters	119B total / 6.5B active (MoE)	27B dense VLM (Gated DeltaNet hybrid)
Reasoning levels
Reasoning levels	Not verifiedUnverified	low, medium, xhigh
Modalities
Modalities	text, image	text, image, video
License
License	Apache 2.0	Apache 2.0
API model id
API model id	mistral-small-2603	qwen3.8-27b
Released
Released	March 16, 2026	August 13, 2026
Artificial Analysis Intelligence Index (2026-09-26)
Artificial Analysis Intelligence Index (2026-09-26)	11.3	Not verifiedUnverified
Artificial Analysis Intelligence Index [xhigh] (2026-09-26)
Artificial Analysis Intelligence Index [xhigh] (2026-09-26)	Not verifiedUnverified	33.7

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

2026-09-26
Artificial Analysis
Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.
Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.

Pricing tiers

Mistral Small 4: Mistral first-party API $0.15/$0.60 per MTok. Open weights (Apache 2.0). 119B total / 6.5B active MoE.

Qwen 3.8 27B: Hosted qwen3.8-27b lists $0.50/$3.00 per MTok on Alibaba Cloud Model Studio (API launched 2026-08-19). Open weights (Apache 2.0) for self-hosting.

BudgetOpen weightsRecord checked September 26, 2026

Mistral Small 4

Mistral Small 4 is Mistral's low-cost Apache-2.0 MoE — 6.5B active parameters with a 256K context and image input.

Best for

Cheap EU-hosted inference
Open-weight self-hosting
High-volume extraction

Watch out

Small active size: not for hard reasoning or agentic coding; max output is not published.

BudgetOpen weightsRecord checked September 26, 2026

Qwen 3.8 27B

Qwen 3.8 27B is Alibaba's compact deployment-friendly dense VLM — 262K native context (1M via YaRN), Apache 2.0 weights, distinct from the hosted Qwen 3.8 Max API.

Best for

Self-hosting on a single node
Multimodal input at small scale
Long-context on modest hardware

Watch out

Dense 27B means higher memory per token than an MoE of equal active size; video input is multimodal-input only.

When the cheaper one wins

Mistral Small 4 is cheaper on output at $0.60 per million tokens against $3 for Qwen 3.8 27B — about 5.0×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

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Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

Pricing verified on both sides — Input and output rates are verified for both models.
3/5 core specs verified on both sides — Not published for at least one side: max output, reasoning levels.
1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
Verified within the last 90 days — Newest catalog check was 2 days ago.
Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Mistral Small 4: Mistral docs — Mistral Small 4 (26.03) (accessed 2026-09-26)
Mistral Small 4: Mistral changelog (accessed 2026-09-26)
Qwen 3.8 27B: HuggingFace — Qwen3.8-27B model card (accessed 2026-08-29)
Qwen 3.8 27B: LiveBench Leaderboard (Qwen 3.8 27B row) (accessed 2026-08-29)
Qwen 3.8 27B: Alibaba Cloud Model Studio pricing (qwen3.8-27b $0.50/$3.00) (accessed 2026-09-26)

Related comparisons

Diving deeper on one model? Mistral Small 4 · Qwen 3.8 27B

Common questions

Mistral Small 4 vs Qwen 3.8 27B

Answered from the verified figures on this page rather than general guidance.

Is Mistral Small 4 or Qwen 3.8 27B cheaper for input?

Mistral Small 4 is cheaper at $0.15 per million input tokens, against $0.50 for Qwen 3.8 27B — roughly 3.3× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Mistral Small 4 has tiered pricing: Mistral first-party API $0.15/$0.60 per MTok. Open weights (Apache 2.0). 119B total / 6.5B active MoE. Qwen 3.8 27B has tiered pricing: Hosted qwen3.8-27b lists $0.50/$3.00 per MTok on Alibaba Cloud Model Studio (API launched 2026-08-19). Open weights (Apache 2.0) for self-hosting.

Is Mistral Small 4 or Qwen 3.8 27B cheaper for output?

Mistral Small 4 is cheaper at $0.60 per million output tokens, against $3 for Qwen 3.8 27B — roughly 5.0× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Mistral Small 4 has tiered pricing: Mistral first-party API $0.15/$0.60 per MTok. Open weights (Apache 2.0). 119B total / 6.5B active MoE. Qwen 3.8 27B has tiered pricing: Hosted qwen3.8-27b lists $0.50/$3.00 per MTok on Alibaba Cloud Model Studio (API launched 2026-08-19). Open weights (Apache 2.0) for self-hosting.

Which has the larger context window, Mistral Small 4 or Qwen 3.8 27B?

Both accept about 262K tokens of context, so document length will not decide between them.

Should I use Mistral Small 4 or Qwen 3.8 27B?

Both sit in the budget tier, so the choice usually comes down to price and context rather than capability. Mistral Small 4 suits cheap eu-hosted inference; Qwen 3.8 27B suits self-hosting on a single node.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

Input price: Mistral Small 4 costs $0.15 per 1M tokens versus $0.50 for Qwen 3.8 27B — a 3.3x difference at the headline tier.

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