Model comparison
K-Exaone vs Mistral Medium 3.5 128B
Head-to-head evidence from 15 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: K-Exaone #143 (Estimated); Mistral Medium 3.5 128B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. K-Exaone and Mistral Medium 3.5 128B share 15 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to K-Exaone; 10 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 15
- K-Exaone only
- 0
- Mistral Medium 3.5 128B only
- 10
- Comparable categories
- 0 / 8
Benchmark data for K-Exaone and Mistral Medium 3.5 128B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 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.
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 | K-Exaone | Δ | Mistral Medium 3.5 128B |
|---|---|---|---|
| Coding | K-ExaoneNot measured | MarginNo overlap | Mistral Medium 3.5 128B77.6 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | K-Exaone | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | K-ExaoneNot available | Mistral Medium 3.5 128B$1.5 input / $7.5 output | A complete price comparison is not available. |
| Generation speedtokens per second | K-ExaoneNot available | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | K-ExaoneNot available | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | K-Exaone256K | Mistral Medium 3.5 128B256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | K-Exaone | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 74.3% | 94.2% | Mistral Medium 3.5 128B leads |
| AA Agentic IndexSource | 8.0% | 19.0% | Mistral Medium 3.5 128B leads |
| GDPval-AASource | 4.9% | 21.6% | Mistral Medium 3.5 128B leads |
| GDPval-AASource | 598 | 933 | Mistral Medium 3.5 128B leads |
| τ³-bench resultsSource | — | 91.4% | Not comparable |
| Gert LabsSource | — | 39.10% | Not comparable |
| AA EnterpriseOps-GymSource | — | 33.7% | Not comparable |
| AA Harvey LABSource | — | 69.1% | Not comparable |
| terminalBenchHardSource | — | 33.3% | Not comparable |
| AA BriefcaseSource | — | 516 | Not comparable |
| AA Tau3 BankingSource | — | 14.4% | Not comparable |
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | K-Exaone | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 22.1% | 29.9% | Mistral Medium 3.5 128B leads |
| AA-GPQA DiamondSource | 78.3% | 74.8% | K-Exaone leads |
| AA-HLESource | 13.1% | 12.8% | K-Exaone leads |
| AA-Omniscience IndexSource | -57.9% | -36.3% | Mistral Medium 3.5 128B leads |
| AA-Omniscience AccuracySource | 16.5% | 25.1% | Mistral Medium 3.5 128B leads |
| AA-Omniscience Hallucination RateSource | 89.1% | 82.0% | Mistral Medium 3.5 128B leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Multimodal1 benchmarks
| Benchmark | K-Exaone | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | — | 64.9% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | K-Exaone | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | 64.7% | 68.8% | Mistral Medium 3.5 128B leads |
Frequently Asked Questions (3)
Can I compare K-Exaone 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 K-Exaone and Mistral Medium 3.5 128B today?
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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