Kimi K2 Thinking vs Qwen3 Coder 480B A35B
Moonshot AIQwenboth via one key, provider price + 3%
Kimi K2 Thinking is Moonshot AI's trillion-parameter MoE reasoning model, released November 2025 with mandatory reasoning baked in. Qwen3 Coder 480B A35B is Qwen's MoE model tuned specifically for agentic coding — function calling, tool use, long-context work — released July 2025. Both are text-only, both run on OpenKey with one key and a flat 3% fee on provider list price. The real differences show up in context length, price, and what each model was actually built to do.
Spec vs spec
| Spec | Kimi K2 Thinking | Qwen3 Coder 480B A35B |
|---|---|---|
| Context window | 262K | 1.0M |
| Max output | 100K | 66K |
| Input modalities | text | text |
| Output modalities | text | text |
| Knowledge cutoff | — | Jun 30, 2025 |
| Released | Nov 6, 2025 | Jul 23, 2025 |
| Reasoning | always on | — |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
moonshotai/kimi-k2-thinking
Input · 1M tokens
$0.600 + 3%$0.618
Output · 1M tokens
$2.50 + 3%$2.58
Cache read · 1M tokens
$0.150 + 3%$0.154
FEE — FLAT, EVERY MODEL3%
qwen/qwen3-coder
Input · 1M tokens
$0.220 + 3%$0.227
Output · 1M tokens
$1.80 + 3%$1.85
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
moonshotai/kimi-k2-thinking
$11.33
$11.00 provider + 3%
qwen/qwen3-coderCheaper
$5.97
$5.80 provider + 3%
Benchmarks
Design Arena categories where both models have results. Higher Elo and lower rank win.
| Kimi K2 Thinking | Qwen3 Coder 480B A35B | |||
|---|---|---|---|---|
| Category | Elo | Rank | Elo | Rank |
| Websites | 1156 | #70 | 1201 | #55 |
Head-to-head preference voting. How we filter and rank
Pricing math
Provider list price: Kimi K2 Thinking runs $0.60/1M input, $2.50/1M output, plus a $0.15/1M cache-read rate Qwen3 Coder doesn't offer. Qwen3 Coder runs $0.22/1M input, $1.80/1M output. On OpenKey (provider price x 1.03), that's $0.618/$2.575 for Kimi K2 Thinking and $0.2266/$1.854 for Qwen3 Coder. On a 10M-input / 2M-output workload, Kimi K2 Thinking costs $11.00 and Qwen3 Coder costs $5.80 — Qwen3 Coder is roughly half the price for the same volume. The input price ratio alone is 2.73x in Qwen3 Coder's favor. If your workload is input-heavy (large repos, long prompts), that ratio compounds fast.
Context and long-document work
Qwen3 Coder ships a 1,048,576-token context window against Kimi K2 Thinking's 262,144 — a 4x gap (context ratio 0.25 when comparing Kimi to Qwen3 Coder). If you're feeding in whole codebases, large monorepos, or long chat histories, Qwen3 Coder has room Kimi K2 Thinking doesn't. Max output tokens run the other way but by less: Kimi K2 Thinking caps at 100,352 tokens per completion, Qwen3 Coder at 65,536. So Kimi K2 Thinking can generate somewhat longer single responses, but Qwen3 Coder can hold far more context before it needs to.
Coding and agentic benchmarks
Qwen3 Coder has Design Arena scores across five categories: codecategories (elo 1192, 61.2% win rate, rank 54), website (elo 1201, 61.7% win rate, rank 55), uicomponent (elo 1170, 61.5% win rate, rank 56), gamedev (elo 1167, 59% win rate, rank 58), and dataviz (elo 1126, 54.9% win rate, rank 74). Kimi K2 Thinking has one Design Arena entry, website (elo 1156, 48.8% win rate, rank 70) — lower elo and win rate than Qwen3 Coder's website score. On Artificial Analysis, Kimi K2 Thinking posts an intelligence index of 17.3, coding index of 21, and agentic index of 1.8; Qwen3 Coder has no Artificial Analysis data in this comparison, so that axis isn't a fair fight either way.
When to pick each
Pick Qwen3 Coder 480B A35B when you're doing high-volume coding tasks, need the larger context window for whole-repo analysis, or care about cost per token — it wins on all three fronts here. Pick Kimi K2 Thinking when your task needs its mandatory reasoning mode for multi-step agentic planning, or when you're specifically testing against its Artificial Analysis coding index of 21. Kimi K2 Thinking is also newer (November 2025 vs July 2025), so it reflects a more recent training cutoff, though no explicit knowledge cutoff date is listed for it while Qwen3 Coder's is 2025-06-30.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| Whole-repo refactors | Qwen3 Coder 480B A35B | 1,048,576-token context vs 262,144 — 4x more room for large codebases |
| High-volume API calls | Qwen3 Coder 480B A35B | $5.80 vs $11.00 on a 10M-in/2M-out workload |
| Multi-step agentic reasoning | Kimi K2 Thinking | mandatory reasoning mode built into the model |
| UI component generation | Qwen3 Coder 480B A35B | Design Arena uicomponent elo 1170, 61.5% win rate vs no equivalent score for Kimi |
| Long single-response output | Kimi K2 Thinking | 100,352 max completion tokens vs 65,536 |
| Website generation benchmarks | Qwen3 Coder 480B A35B | elo 1201 / 61.7% win rate vs Kimi's elo 1156 / 48.8% win rate on the same category |
Questions
- Which model is cheaper for a typical workload?
- Qwen3 Coder 480B A35B. On a 10M-input / 2M-output workload it costs $5.80 versus $11.00 for Kimi K2 Thinking — roughly half, driven by a 2.73x lower input price ($0.22 vs $0.60 per 1M tokens at provider rates).
- Which has the bigger context window?
- Qwen3 Coder 480B A35B, by a wide margin: 1,048,576 tokens versus Kimi K2 Thinking's 262,144 — a 4x difference (context ratio 0.25).
- Does Kimi K2 Thinking beat Qwen3 Coder on coding benchmarks?
- Not on the overlapping category. Both have Design Arena website scores — Qwen3 Coder posts elo 1201 with a 61.7% win rate (rank 55) while Kimi K2 Thinking posts elo 1156 with a 48.8% win rate (rank 70).
- Can I use both models with the same API key?
- Yes. Both Kimi K2 Thinking and Qwen3 Coder 480B A35B run on OpenKey with a single API key, and pricing is provider list price plus a flat 3% fee on both.