Coding
Directional only- Composer 2
- 51.3
- Estimated · #65/183
- Mistral Medium 3
- 38.2
- Estimated · #147/183
- Basis
- BenchAlign lane · 4 vs 0 public rows
- Reading
- Directional only
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
See the free Radar BriefUpdated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
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 resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Prompts that approach the documented context limit
Composer 2
Composer 2 has the larger documented context window.
Confidence: documented
1K fresh input + 500 output tokens
Mistral Medium 3
Mistral Medium 3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
50K fresh input + 3K output tokens
Mistral Medium 3
Mistral Medium 3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Composer 2 and Mistral Medium 3 are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Mistral Medium 3 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
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. Composer 2 does not fit this workload in one request. Mistral Medium 3 does not fit this workload in one request. Composer 2 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
| Category | Composer 2 | Mistral Medium 3 | Basis | Reading |
|---|---|---|---|---|
| Coding | 51.3Estimated · #65/183 | 38.2Estimated · #147/183 | Directional onlyBenchAlign lane · 4 vs 0 public rows | Directional only |
| Agentic | 51.3Estimated · #55/151 | Not ranked | Not comparableBenchAlign lane · 1 vs 0 public rows | Not comparable |
| Reasoning | Not ranked | 43.8Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | 36.6Estimated · #154/181 | Not comparableBenchAlign lane · 0 vs 0 public rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 38.1Unranked · 1 rankable row | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 45.5#90/120 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
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.
1K fresh input + 500 output tokens
Mistral Medium 3 has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Mistral Medium 3 has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Composer 2 does not fit this workload in one request. Mistral Medium 3 does not fit this workload in one request. Composer 2 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Composer 2
200K
Mistral Medium 3
128K
Composer 2
Not sourced
Mistral Medium 3
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Composer 2
Not published
Mistral Medium 3
Not published
Composer 2
Not sourced
Mistral Medium 3
Not sourced
Composer 2
Not sourced
Mistral Medium 3
Not sourced
Composer 2
Not sourced
Mistral Medium 3
Not sourced
Composer 2
Reasoning
Mistral Medium 3
Non-Reasoning
Composer 2
Proprietary
Mistral Medium 3
Proprietary
Composer 2
Proprietary
Mistral Medium 3
Proprietary
Composer 2
2026-03-19
Mistral Medium 3
2026-02-20
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 2.0
Not directly comparable
SWE Multilingual
Not directly comparable
SWE-Rebench
Not directly comparable
React Native Evals
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
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.
Composer 2 scores higher for coding on the public lane, 51.3 to 38.2. Composer 2 and Mistral Medium 3 are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Mistral Medium 3 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
For the stated presets, chat costs $0.00175 on Composer 2 and $0.0014 on Mistral Medium 3; repository review costs $0.0325 and $0.026; the cache-heavy agent loop costs $0.135 and $0.108. Composer 2 does not fit this workload in one request. Mistral Medium 3 does not fit this workload in one request. Composer 2 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate.
Composer 2 has the larger documented context window: 200K, compared with 128K.
Last updated September 4, 2026
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