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#79

Mistral Small 4

Mistral Release: 2026-03-16 Tested on: 2026-04-11 01:44 mistralai/mistral-small-2603::medium
119B total (6B active)MoEOpen source
(medium) (none)

Summary

Mistral Small 4 scores 5.7 on AI BENCHY and ranks #79. It has N/A reliability, a 50.0% pass rate, $0.034 total cost, and 5.64s average response time.

What makes Mistral Small 4 unique: Its total benchmark cost is unusually low for its score range. It is notably fast compared with similar models.

Model facts

Researched on 2026-08-12

Reported
Parameters
119B total (6B active)
Architecture
MoE
Availability
Open source
License
Apache-2.0

The vendor also reports 8B active when embeddings are included; UI uses routed active parameters.

Score

5.7

Consistency

6.8

Reliability

N/A

Total Output Tokens

54,492

Total Input Tokens

0

Input Price

$0.150 / 1M

Output Price

$0.600 / 1M

Tests Correct

Wrong Tests: 13

Attempt pass rate: 50.0%

Flaky tests

7

Flaky tests had mixed outcomes across runs (at least one pass and one fail).

Response Time (avg)

5.64s

Response Time (max): 30.49s

Response Time (total): 101.52s

Hamster playing table tennis

Prompt: Create a detailed SVG illustration of a hamster playing table tennis.

#79 Mistral Small 4

medium
Cost
$0.006
Time
47.9s
Tokens
9,857 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-08-14 02:05 Re-test 5.1 10.0 $0.097 Compare
2026-07-16 22:23 New test added 5.1 10.0 $0.096 Compare
2026-06-04 13:43 New test added 5.3 10.0 $0.068 Compare
2026-05-22 00:16 Suite changed 5.4 10.0 $0.056 Compare
2026-04-11 01:44 First recorded run 5.7 N/A $0.034 Current run

Run comparison

RunBenchmark coverageScoreConsistencyReliabilityTests CorrectFlaky testsTotal Output TokensTotal Input TokensTotal CostResponse Time (avg)
2026-04-11 01:44 · First recorded run54/54 attempts5.76.8N/A5/18754,4920$0.0345.64s
2026-08-14 02:05 · Re-test66/66 attempts5.17.010.05/228133,597140,559$0.09710.80s
Difference+0.5-0.20-1-79105-140559-$0.063-5160ms

Benchmark coverage differs: 54/54 attempts (Target: 3 repeats per test) versus 66/66 attempts (Target: 3 repeats per test). Totals and repeat-sensitive metrics are not directly comparable.

These two runs used different benchmark suites, so the deltas reflect both model changes and suite changes.

Charts

Choose the first model, then click a second model to open a side-by-side page.

Total Output Tokens

Score vs Total Output Tokens

Quick Compare

Category Breakdown

Category Score Consistency Tests Correct
Anti-AI Tricks 5.6 3.8
Coding 6.7 3.5
Combined 3.0 10.0
Data parsing and extraction 7.3 5.9
Domain specific 5.3 7.2
General Intelligence 4.8 10.0
Instructions following 7.3 5.8
Puzzle Solving 3.4 9.7
Tool Calling 10.0 10.0

Compared models