Pairwise benchmark snapshot · Aug 1, 2026
In this head-to-head showdown, Yi-Large delivers higher overall intelligence and human-preferred responses (Elo 1,430 vs 1,420), while Yi-Large leads in SWE-bench software engineering benchmarks (53.8%), while Yi-Large is more budget-friendly at $0.3/1M per 1M output tokens, while Kimi Chat 1.5 provides faster response streaming (95 tok/s). Review the complete breakdown below to determine which model best fits your performance and budget requirements.
10 direct benchmark disciplines evaluated across capability, speed, and cost
Moonshot ultra-long context model supporting up to 2 million tokens per request.
01.AI full-scale dense model for complex instruction following.
Currently comparing Kimi Chat 1.5 vs Yi-Large. Alternative family tiers available.
Δ 10 Arena Elo pts
95 tok/s
$0.3 / 1M output
Relative percentile scores computed across all active models in the benchmark catalog.
Comparing top Western standard models with China's leading frontier rival across 6 skill dimensions. Tap any spoke or dot to inspect.
Category wins across reasoning intelligence, generation speed, and token cost.
Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy
Generation throughput and time to first token responsiveness
Cost per million tokens and max context window length
| Benchmark | Kimi Chat 1.5 | Yi-Large | Advantage Delta |
|---|---|---|---|
| Preference Elo | +10 | ||
| Coding Elo | +20 | ||
| LiveBench | +2.5% | ||
| SWE-bench | +2.8% | ||
| GPQA Diamond | +0.9% | ||
| Time to first token | +10 ms | ||
| Output speed | 95 tok/s | 90 tok/s | +5 tok/s |
| Input price | $0.2/1M | $0.3/1M | +$0.1/1M |
| Output price | $0.8/1M | $0.3/1M | +$0.5/1M |
| Context window | +2M |
Simulate monthly production API costs in USD (US Dollar).
Yi-Large is estimated to save $4.00/month ($48/year).
Higher SWE-bench (53.8%).
Lower output list price ($0.3/1M).
Lower TTFT (210 ms).
Larger window (2M).
Yi-Large is the side marked multimodal in the catalog.
| Target Workload | Recommended Pick | Evaluation Rationale |
|---|---|---|
| Repo / coding agents | Yi-Large | Higher SWE-bench (53.8%). |
| High-volume chat | Yi-Large | Lower output list price ($0.3/1M). |
| Voice / low-latency UI | Kimi Chat 1.5 | Lower TTFT (210 ms). |
| Long-document RAG | Kimi Chat 1.5 | Larger window (2M). |
| Screenshots / vision | Yi-Large | Yi-Large is the side marked multimodal in the catalog. |
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Verified Head-to-Head Telemetry
