Agentic
Not comparable- Grok 4.3
- Not measured
- Mistral Medium 3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Model comparison
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.
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
Grok 4.3
Grok 4.3 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
No shared weighted benchmark basis supports a winner.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
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. 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.
Confidence: rate-fallback
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
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.
| Category | Grok 4.3 | Mistral Medium 3 | 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 |
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
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.
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.
Grok 4.3
1M
Mistral Medium 3
128K
Grok 4.3
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.
Grok 4.3
$0.2 per 1M cached input tokens
Mistral Medium 3
Not published
Grok 4.3
Not sourced
Mistral Medium 3
Not sourced
Grok 4.3
Not sourced
Mistral Medium 3
Not sourced
Grok 4.3
Not sourced
Mistral Medium 3
Not sourced
Grok 4.3
Reasoning
Mistral Medium 3
Non-Reasoning
Grok 4.3
Proprietary
Mistral Medium 3
Proprietary
Grok 4.3
Proprietary
Mistral Medium 3
Proprietary
Grok 4.3
2026-04-30
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.
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.
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
For the stated presets, chat costs $0.0025 on Grok 4.3 and $0.0014 on Mistral Medium 3; repository review costs $0.07 and $0.026; the cache-heavy agent loop costs $0.09 and $0.108. 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.
Grok 4.3 has the larger documented context window: 1M, compared with 128K.
Last updated July 30, 2026
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