Model comparison
Kimi K3 vs Mistral Medium 3.5 128B
Head-to-head evidence from 18 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Kimi K3 #4 (Supported); Mistral Medium 3.5 128B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K3 and Mistral Medium 3.5 128B share 18 comparable benchmark results. 0 of 8 categories are comparable. 39 results are unique to Kimi K3; 7 to Mistral Medium 3.5 128B.
Updated July 23, 2026- Shared results
- 18
- Kimi K3 only
- 39
- Mistral Medium 3.5 128B only
- 7
- Comparable categories
- 0 / 8
Benchmark data for Kimi K3 and Mistral Medium 3.5 128B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Kimi K3 is priced at $3.00 input / $15.00 output per 1M tokens, versus $1.50 input / $7.50 output per 1M tokens for Mistral Medium 3.5 128B. Kimi K3 has the larger context window at 1.05M, compared with 256K for Mistral Medium 3.5 128B.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Kimi K3 | Δ | Mistral Medium 3.5 128B |
|---|---|---|---|
| Agentic | Kimi K389.5 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Coding | Kimi K3Not measured | MarginNo overlap | Mistral Medium 3.5 128B77.6 |
| Knowledge | Kimi K361.0 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Multimodal | Kimi K378.5 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K3 | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K3$3 input / $15 output | Mistral Medium 3.5 128B$1.5 input / $7.5 output | Mistral Medium 3.5 128B has the lower combined listed price. |
| Generation speedtokens per second | Kimi K3Not available | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K3Not available | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K31.05M | Mistral Medium 3.5 128B256K | Kimi K3 lists the larger context window. |
Benchmark Deep Dive
Agentic25 benchmarks
| Benchmark | Kimi K3 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 88.3% | — | Not comparable |
| BrowseCompSource | 91.2% | — | Not comparable |
| DeepSearchQASource | 95.0% | — | Not comparable |
| Toolathlon-VerifiedSource | 73.2% | — | Not comparable |
| MCP AtlasSource | 84.2% | — | Not comparable |
| AutomationBenchSource | 30.8% | — | Not comparable |
| JobBenchSource | 52.9% | — | Not comparable |
| APEX-AgentsSource | 37.6% | — | Not comparable |
| SpreadsheetBench 2Source | 34.8% | — | Not comparable |
| DECK-BenchSource | 73.5% | — | Not comparable |
| AA Agentic IndexSource | 50.1% | 19.0% | Kimi K3 leads |
| GDPval-AASource | 59.0% | 21.4% | Kimi K3 leads |
| GDPval-AASource | 1679 | 929 | Kimi K3 leads |
| AA BriefcaseSource | 1543 | 506 | Kimi K3 leads |
| AA AutomationBenchSource | 52.7% | — | Not comparable |
| AA EnterpriseOps-GymSource | 45.3% | 33.7% | Kimi K3 leads |
| AA Harvey LABSource | 94.6% | 69.1% | Kimi K3 leads |
| AA Tau3 BankingSource | 33.4% | 14.4% | Kimi K3 leads |
| aaTerminalBench21Source | 85% | — | Not comparable |
| APEX-Agents-AASource | 41.3% | — | Not comparable |
| AA ITBenchSource | 47.7% | — | Not comparable |
| τ³-bench resultsSource | — | 91.4% | Not comparable |
| τ²-bench resultsSource | — | 94.2% | Not comparable |
| Gert LabsSource | — | 39.10% | Not comparable |
| terminalBenchHardSource | — | 33.3% | Not comparable |
Coding10 benchmarks
| Benchmark | Kimi K3 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| deepSweSource | 67.5% | — | Not comparable |
| FrontierSWESource | 81.2% | — | Not comparable |
| ProgramBenchSource | 77.8% | — | Not comparable |
| Kimi Code Bench v2Source | 72.9% | — | Not comparable |
| sweMarathonSource | 42% | — | Not comparable |
| PostTrain BenchSource | 36.6% | — | Not comparable |
| MLS-Bench LiteSource | 48.3% | — | Not comparable |
| AA Coding IndexSource | 76.2% | 46.9% | Kimi K3 leads |
| AA-SciCodeSource | 58.7% | 39.6% | Kimi K3 leads |
| SWE-bench VerifiedSource | — | 77.6% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Kimi K3 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| GPQASource | 93.5% | — | Not comparable |
| GPQA-DSource | 93.5% | — | Not comparable |
| HLESource | 56% | — | Not comparable |
| HLE w/o toolsSource | 43.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 57.1% | 29.9% | Kimi K3 leads |
| AA-GPQA DiamondSource | 93.5% | 74.8% | Kimi K3 leads |
| AA-HLESource | 44.3% | 12.8% | Kimi K3 leads |
| AA-Omniscience IndexSource | 18.4% | -36.3% | Kimi K3 leads |
| AA-Omniscience AccuracySource | 46.0% | 25.1% | Kimi K3 leads |
| AA-Omniscience Hallucination RateSource | 50.9% | 82.0% | Kimi K3 leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Multimodal15 benchmarks
| Benchmark | Kimi K3 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| OfficeQA ProSource | 63.3% | — | Not comparable |
| MMMU-ProSource | 81.6% | — | Not comparable |
| MMMU-Pro w/ PythonSource | 83.4% | — | Not comparable |
| CharXiv w/o toolsSource | 84.8% | — | Not comparable |
| CharXivSource | 91.3% | — | Not comparable |
| MathVisionSource | 94.3% | — | Not comparable |
| MathVision w/ PythonSource | 97.8% | — | Not comparable |
| BabyVision w/ PythonSource | 85.7% | — | Not comparable |
| ZeroBenchSource | 23.0% | — | Not comparable |
| ZeroBench w/ PythonSource | 41.0% | — | Not comparable |
| WorldVQA ForceAnswerSource | 51.0% | — | Not comparable |
| OmniDocBenchSource | 91.1% | — | Not comparable |
| PerceptionBenchSource | 58.5% | — | Not comparable |
| AA-MMMU-ProSource | 80.5% | 64.9% | Kimi K3 leads |
| Design Arena WebsiteSource | 1386 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Kimi K3 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 68.8% | Not comparable |
Frequently Asked Questions (3)
Can I compare Kimi K3 and Mistral Medium 3.5 128B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Kimi K3 and Mistral Medium 3.5 128B today?
Kimi K3: $3.00 input / $15.00 output per 1M tokens Mistral Medium 3.5 128B: $1.50 input / $7.50 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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