Model comparison
GPT-4o mini vs Kimi K2.7 Code
Head-to-head evidence from 9 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-4o mini #192 (Supported); Kimi K2.7 Code #92 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4o mini and Kimi K2.7 Code share 9 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to GPT-4o mini; 14 to Kimi K2.7 Code.
Updated July 27, 2026- Shared results
- 9
- GPT-4o mini only
- 1
- Kimi K2.7 Code only
- 14
- Comparable categories
- 0 / 8
Benchmark data for GPT-4o mini and Kimi K2.7 Code is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 9 shared benchmark results across 4 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 K2.7 Code is priced at $0.95 input / $4.00 output per 1M tokens, versus $0.15 input / $0.60 output per 1M tokens for GPT-4o mini. Kimi K2.7 Code has the larger context window at 256K, compared with 128K for GPT-4o mini.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4o mini | Kimi K2.7 Code | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4o mini$0.15 input / $0.6 output | Kimi K2.7 Code$0.95 input / $4 output | GPT-4o mini has the lower combined listed price. |
| Generation speedtokens per second | GPT-4o mini33 tok/s | Kimi K2.7 CodeNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-4o mini3.16 s | Kimi K2.7 CodeNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-4o mini128K | Kimi K2.7 Code256K | Kimi K2.7 Code lists the larger context window. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | GPT-4o mini | Kimi K2.7 Code | Result |
|---|---|---|---|
| AA Agentic IndexSource | 1.0% | 29.6% | Kimi K2.7 Code leads |
| GDPval-AASource | 0.0% | 34.3% | Kimi K2.7 Code leads |
| GDPval-AASource | 241 | 1186 | Kimi K2.7 Code leads |
| Kimi Claw 24/7Source | — | 46.9% | Not comparable |
| MCP AtlasSource | — | 76% | Not comparable |
| MCP Mark VerifiedSource | — | 81.1% | Not comparable |
| τ²-bench resultsSource | — | 90.1% | Not comparable |
Coding6 benchmarks
| Benchmark | GPT-4o mini | Kimi K2.7 Code | Result |
|---|---|---|---|
| AA-SciCodeSource | 22.9% | 47.5% | Kimi K2.7 Code leads |
| AA Coding IndexSource | 11.4% | 60.8% | Kimi K2.7 Code leads |
| Kimi Code Bench v2Source | — | 62.0% | Not comparable |
| ProgramBenchSource | — | 53.6% | Not comparable |
| MLS-Bench LiteSource | — | 35.1% | Not comparable |
| cursorBench32Source | — | 49.7% | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GPT-4o mini | Kimi K2.7 Code | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 6.9% | 42.0% | Kimi K2.7 Code leads |
| AA-GPQA DiamondSource | 42.6% | 89.6% | Kimi K2.7 Code leads |
| AA-HLESource | 4.0% | 32.8% | Kimi K2.7 Code leads |
| AA-Omniscience IndexSource | — | -10.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 38.6% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 80.3% | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-4o mini | Kimi K2.7 Code | Result |
|---|---|---|---|
| AA-IFBenchSource | 31.0% | 63.1% | Kimi K2.7 Code leads |
Frequently Asked Questions (3)
Can I compare GPT-4o mini and Kimi K2.7 Code 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 GPT-4o mini and Kimi K2.7 Code today?
GPT-4o mini: $0.15 input / $0.60 output per 1M tokens Kimi K2.7 Code: $0.95 input / $4.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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