Pairwise benchmark snapshot · Aug 17, 2026
In this head-to-head showdown, Kimi K3 delivers higher overall intelligence and human-preferred responses (Elo 1,528 vs 1,495), while Kimi K3 leads in SWE-bench software engineering benchmarks (73.8%), while Qwen QwQ 32B is more budget-friendly at $1.2/1M per 1M output tokens, while Kimi K3 provides faster response streaming (68 tok/s). Review the complete breakdown below to determine which model best fits your performance and budget requirements.
9 direct benchmark disciplines evaluated across capability, speed, and cost
Moonshot AI frontier flagship reasoning and agent swarm model with 256k context and top-tier SWE-bench coding capability.
Alibaba specialized open reasoning model competing with frontier closed reasoning models.
Currently comparing Kimi K3 vs Qwen QwQ 32B. Alternative family tiers available.
Simulate accuracy gains vs added response time & token cost
Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.
Simulate accuracy gains vs added response time & token cost
Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.
Δ 33 Arena Elo pts
68 tok/s
$1.2 / 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 K3 | Qwen QwQ 32B | Advantage Delta |
|---|---|---|---|
| Preference Elo | +33 | ||
| Coding Elo | +15 | ||
| LiveBench | +1.5% | ||
| SWE-bench | +6.3% | ||
| GPQA Diamond | +5.2% | ||
| Time to first token | +30 ms | ||
| Output speed | 68 tok/s | 68 tok/s | — |
| Input price | $0.3/1M | +$2.7/1M | |
| Output price | $1.2/1M | +$13.8/1M | |
| Context window | +918k |
Simulate monthly production API costs in USD (US Dollar).
Qwen QwQ 32B is estimated to save $301.50/month ($3,618/year).
Higher SWE-bench (73.8%).
Lower output list price ($1.2/1M).
Lower TTFT (290 ms).
Larger window (1M).
Kimi K3 is the side marked multimodal in the catalog.
| Target Workload | Recommended Pick | Evaluation Rationale |
|---|---|---|
| Repo / coding agents | Kimi K3 | Higher SWE-bench (73.8%). |
| High-volume chat | Qwen QwQ 32B | Lower output list price ($1.2/1M). |
| Voice / low-latency UI | Kimi K3 | Lower TTFT (290 ms). |
| Long-document RAG | Kimi K3 | Larger window (1M). |
| Screenshots / vision | Kimi K3 | Kimi K3 is the side marked multimodal in the catalog. |
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