Agentic
Not comparable- Mistral Medium 3
- Not measured
- Mistral Small 4 (Reasoning)
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Model comparison
Mistral Medium 3 vs Mistral Small 4 (Reasoning)
Updated July 30, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.
0 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Long documents
Prompts that approach the documented context limit
Mistral Small 4 (Reasoning)
Mistral Small 4 (Reasoning) has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Mistral Small 4 (Reasoning)
Mistral Small 4 (Reasoning) has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Mistral Small 4 (Reasoning)
Mistral Small 4 (Reasoning) has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Mistral Medium 3 does not fit this workload in one request. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Small 4 (Reasoning) has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
Evidence parity totals are not available.
- Shared results
- 0
- Mistral Medium 3 only
- 0
- Mistral Small 4 (Reasoning) only
- 0
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Not comparable- Mistral Medium 3
- Not measured
- Mistral Small 4 (Reasoning)
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Mistral Medium 3
- Not measured
- Mistral Small 4 (Reasoning)
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Mistral Medium 3
- Not measured
- Mistral Small 4 (Reasoning)
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Mistral Medium 3
- Not measured
- Mistral Small 4 (Reasoning)
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Mistral Medium 3
- Not measured
- Mistral Small 4 (Reasoning)
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Mistral Medium 3
- Not measured
- Mistral Small 4 (Reasoning)
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Mistral Medium 3
- Not measured
- Mistral Small 4 (Reasoning)
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Mistral Medium 3 | Mistral Small 4 (Reasoning) | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Coding | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Mistral Medium 3
- $0.0014
- Fits in one request
- Mistral Small 4 (Reasoning)
- $0.00045
- Fits in one request
Mistral Small 4 (Reasoning) has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Mistral Medium 3
- $0.026
- Fits in one request
- Mistral Small 4 (Reasoning)
- $0.0093
- Fits in one request
Mistral Small 4 (Reasoning) has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Mistral Medium 3
- $0.108
- Does not fit in one request
- Cached input priced at the published list-input rate
- Mistral Small 4 (Reasoning)
- $0.039
- Fits in one request
- Cached input priced at the published list-input rate
Mistral Medium 3 does not fit this workload in one request. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Small 4 (Reasoning) has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationMistral Medium 3Mistral Small 4 (Reasoning)
Context window
Maximum documented context; output-token limits may be lower.
Mistral Medium 3
128K
Mistral Small 4 (Reasoning)
256K
API model ID
Mistral Medium 3
Not sourced
Mistral Small 4 (Reasoning)
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Mistral Medium 3
Not published
Mistral Small 4 (Reasoning)
Not published
Documented inputs
Mistral Medium 3
Not sourced
Mistral Small 4 (Reasoning)
Not sourced
Documented outputs
Mistral Medium 3
Not sourced
Mistral Small 4 (Reasoning)
Not sourced
Provider availability
Mistral Medium 3
Not sourced
Mistral Small 4 (Reasoning)
Not sourced
Reasoning profile
Mistral Medium 3
Non-Reasoning
Mistral Small 4 (Reasoning)
Reasoning
Weight access
Mistral Medium 3
Proprietary
Mistral Small 4 (Reasoning)
Open Weight
License
Mistral Medium 3
Proprietary
Mistral Small 4 (Reasoning)
Open Weight
Release date
Mistral Medium 3
2026-02-20
Mistral Small 4 (Reasoning)
2026-02-20
If you already use one of these models
- Deployment change
- Both entries list Mistral as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- Repository review: $0.026 vs $0.0093. Cache-heavy agent loop: $0.108 vs $0.039.
- Context tradeoff
- Mistral Small 4 (Reasoning) has the larger documented window (256K).
Run the same representative tasks against both endpoints before changing production traffic.
Frequently asked questions
Which is better, Mistral Medium 3 or Mistral Small 4 (Reasoning)?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Mistral Medium 3 or Mistral Small 4 (Reasoning)?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Mistral Medium 3 or Mistral Small 4 (Reasoning)?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Mistral Medium 3 or Mistral Small 4 (Reasoning)?
For the stated presets, chat costs $0.0014 on Mistral Medium 3 and $0.00045 on Mistral Small 4 (Reasoning); repository review costs $0.026 and $0.0093; the cache-heavy agent loop costs $0.108 and $0.039. Mistral Medium 3 does not fit this workload in one request. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Small 4 (Reasoning) has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Mistral Medium 3 or Mistral Small 4 (Reasoning)?
Mistral Small 4 (Reasoning) has the larger documented context window: 256K, compared with 128K.
Related comparisons
Last updated July 30, 2026
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