Agentic
Not comparable- Mistral Medium 3.5 128B
- Not measured
- Step 3.7 Flash
- 66.4
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Mistral Medium 3.5 128B vs Step 3.7 Flash
Updated August 30, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
1 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.
Chat turn cost
1K fresh input + 500 output tokens
Step 3.7 Flash
Step 3.7 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Step 3.7 Flash
Step 3.7 Flash has the lower estimated token cost for this stated workload. Mistral Medium 3.5 128B has no published cached-input rate, so cached tokens use its listed input rate. Step 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Step 3.7 Flash
Step 3.7 Flash 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
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 Mistral Medium 3.5 128B only
1 Shared
10 Step 3.7 Flash only
- Shared results
- 1
- Mistral Medium 3.5 128B only
- 2
- Step 3.7 Flash only
- 10
- 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 3.5 128B
- 77.6
- Step 3.7 Flash
- 56.3
- Weighted basis
- 1 vs 1 rows
- Reading
- Not comparable
Reasoning
Not comparable- Mistral Medium 3.5 128B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Mistral Medium 3.5 128B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Mistral Medium 3.5 128B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Mistral Medium 3.5 128B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Mistral Medium 3.5 128B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Mistral Medium 3.5 128B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Mistral Medium 3.5 128B | Step 3.7 Flash | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | Not measured | 66.4 | Not comparable0 vs 2 rows | Not comparable |
| Coding | 77.6 | 56.3 | Not comparable1 vs 1 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 3.5 128B
- $0.00525
- Fits in one request
- Step 3.7 Flash
- $0.00077
- Fits in one request
Step 3.7 Flash has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Mistral Medium 3.5 128B
- $0.0975
- Fits in one request
- Step 3.7 Flash
- $0.01345
- Fits in one request
Step 3.7 Flash 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 3.5 128B
- $0.405
- Fits in one request
- Cached input priced at the published list-input rate
- Step 3.7 Flash
- $0.0555
- Fits in one request
- Cached input priced at the published list-input rate
Step 3.7 Flash has the lower modeled cost
Mistral Medium 3.5 128B has no published cached-input rate, so cached tokens use its listed input rate. Step 3.7 Flash 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 3.5 128BStep 3.7 Flash
Context window
Maximum documented context; output-token limits may be lower.
Mistral Medium 3.5 128B
256K
Step 3.7 Flash
256K
API model ID
Mistral Medium 3.5 128B
Not sourced
Step 3.7 Flash
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 3.5 128B
Not published
Step 3.7 Flash
Not published
Documented inputs
Mistral Medium 3.5 128B
Not sourced
Step 3.7 Flash
Not sourced
Documented outputs
Mistral Medium 3.5 128B
Not sourced
Step 3.7 Flash
Not sourced
Provider availability
Mistral Medium 3.5 128B
Not sourced
Step 3.7 Flash
Not sourced
Reasoning profile
Mistral Medium 3.5 128B
Reasoning
Step 3.7 Flash
Reasoning
Weight access
Mistral Medium 3.5 128B
Open Weight
Step 3.7 Flash
Open Weight
License
Mistral Medium 3.5 128B
Open Weight
Step 3.7 Flash
Open Weight
Release date
Mistral Medium 3.5 128B
2026-04-29
Step 3.7 Flash
2026-05-29
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- Repository review: $0.0975 vs $0.01345. Cache-heavy agent loop: $0.405 vs $0.0555.
- Context tradeoff
- Both models list 256K.
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence13 rows
Agentic
τ³-bench results
Mistral Medium 3.5 128B91.4%SourceStep 3.7 Flash—Not directly comparable
Gert Labs
Shared sourceMistral Medium 3.5 128B39.10%Step 3.7 Flash51.57%Step 3.7 Flash leads this result
Terminal-Bench 2.0
Mistral Medium 3.5 128B—Step 3.7 Flash59.5%SourceNot directly comparable
BrowseComp
Mistral Medium 3.5 128B—Step 3.7 Flash75.8%SourceNot directly comparable
DeepSearchQA
Mistral Medium 3.5 128B—Step 3.7 Flash92.8%SourceNot directly comparable
Toolathlon
Mistral Medium 3.5 128B—Step 3.7 Flash49.5%SourceNot directly comparable
Claw-Eval
Mistral Medium 3.5 128B—Step 3.7 Flash67.1%SourceNot directly comparable
HLE w/ tools
Mistral Medium 3.5 128B—Step 3.7 Flash47.2%SourceNot directly comparable
Coding
Multimodal
Frequently asked questions
Which is better, Mistral Medium 3.5 128B or Step 3.7 Flash?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Mistral Medium 3.5 128B or Step 3.7 Flash?
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 3.5 128B or Step 3.7 Flash?
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 3.5 128B or Step 3.7 Flash?
For the stated presets, chat costs $0.00525 on Mistral Medium 3.5 128B and $0.00077 on Step 3.7 Flash; repository review costs $0.0975 and $0.01345; the cache-heavy agent loop costs $0.405 and $0.0555. Mistral Medium 3.5 128B has no published cached-input rate, so cached tokens use its listed input rate. Step 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Mistral Medium 3.5 128B or Step 3.7 Flash?
Both models list the same context window, 256K.
Related comparisons
Last updated August 30, 2026
Watch Mistral Medium 3.5 128B vs Step 3.7 Flash
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.