Kimi K3 wins on coding (96 vs 93). Qwen 3.8 Max wins on price ($2 vs $3/1M input). For most workflows, Kimi K3 is the stronger default — closest chinese challenger to the frontier — #4 overall on intelligence.
The safest Kimi K3 vs Qwen 3.8 Max default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Kimi K3 is the strongest answer here for Kimi K3 vs Qwen 3.8 Max — pick it when quality of output matters more than the $3.00/1M/1M input you pay for it.
Qwen 3.8 Max handles the same job for about 56% less per token. Start here and only move up if the output is not good enough.
Qwen 3.8 Max is the fastest of these for Kimi K3 vs Qwen 3.8 Max — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Kimi K3 leads on coding with a score of 96 vs 93 for Qwen 3.8 Max.
Qwen 3.8 Max is cheaper at $2/1M input tokens vs $3/1M for Kimi K3.
Kimi K3 is the stronger default for reasoning tasks.
Kimi K3 is the safer default: it is built for frontier-level reasoning and agentic coding, which covers most of what people bring to this comparison.
Choose Qwen 3.8 Max when your work is mostly multimodal and vision-heavy workloads at scale — that is the workload it was tuned for.
Qwen 3.8 Max is the more cost-efficient option at $2/1M input — Kimi K3 costs 2x more per input token, so the gap is worth taking seriously wherever token volume rather than peak quality drives the bill.
Switch the scoring lens to see whether the Kimi K3 vs Qwen 3.8 Max answer changes when cost, speed, or long-document depth leads the decision.
Moonshot / Premium / Aug 6, 2026
Closest Chinese challenger to the frontier — #4 overall on intelligence.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need fast responses or predictable output costs — always-on thinking burns tokens.
Where the Kimi K3 vs Qwen 3.8 Max recommendation shifts once you weigh price or latency differently.
Closest Chinese challenger to the frontier — #4 overall on intelligence.
Best Chinese flagship — beats GPT-5.6 Sol on coding, #2 globally for vision.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Kimi K3Moonshot | $3.00/1M | $15.00/1M | $60 | 1M tokens | Deliberate | 96 | 90 | 93 |
| Qwen 3.8 MaxAlibaba | $2.00/1M | $6.00/1M | $32 | 1M tokens | Balanced | 93 | 85 | 88 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for Kimi K3 vs Qwen 3.8 Max, what it is genuinely good at, and where we would steer you away from it.
Our pick for Kimi K3 vs Qwen 3.8 Max. It scores 38/100 on the budget axis we weight this page by, and nothing else in this shortlist matches it on output quality.
Moonshot's 2.8-trillion-parameter multimodal reasoning flagship with always-on thinking — the largest open-weight model ever released and the closest Chinese challenger to the Western frontier.
You need fast responses or predictable output costs — always-on thinking burns tokens.
The first Chinese model to genuinely crowd the Western frontier — #4 on aggregate intelligence ahead of Opus 4.8. The always-on thinking makes it slow and output-heavy, so cost per task runs above the sticker price. A serious Opus-class alternative if latency isn't critical.
Full pricing, benchmark table and release notes on the Kimi K3 page.
Where most budgets should land for Kimi K3 vs Qwen 3.8 Max — about 56% less per token than Kimi K3, and still 64/100 on the budget axis.
Alibaba's largest model ever — a 2.4-trillion-parameter MoE (95B active) multimodal flagship that beat GPT-5.6 Sol on SWE-bench Pro and ranks #2 globally for vision.
You need independently verified benchmarks or Western data residency.
The strongest Chinese multimodal flagship and a legitimate SWE-bench Pro upset over GPT-5.6 Sol. If vision matters, only Fable 5-class models beat it — at 3–8x the price. Wait for independent evals before betting production on the self-reported numbers.
Full pricing, benchmark table and release notes on the Qwen 3.8 Max page.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Kimi K3 wins on more of the categories we score — reasoning, coding, research — so it is the better default of the two. Qwen 3.8 Max is the better pick when your work is mostly multimodal and vision-heavy workloads at scale. Neither is universally "better": Kimi K3 is aimed at frontier-level reasoning and agentic coding, Qwen 3.8 Max at multimodal and vision-heavy workloads at scale.
Qwen 3.8 Max is cheaper at $2/1M input and $6/1M output. Kimi K3 costs $3/1M input and $15/1M output.
Both Kimi K3 and Qwen 3.8 Max have the same 1M context window.
Kimi K3 is better for coding with a score of 96 vs Qwen 3.8 Max's 93 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
Qwen 3.8 Max is faster with a balanced speed rating (score: 3) vs Kimi K3's deliberate rating (score: 2). Speed matters most for interactive and high-throughput work; for batch jobs the Kimi K3 latency penalty is usually invisible.
Most expensive Chinese-lab model ever ($3/$15) with always-on thinking driving high output-token burn and slow responses. 2.8T size makes self-hosting impractical despite open weights; consumer signups were paused July 19 over GPU capacity. Avoid it if you need fast responses or predictable output costs — always-on thinking burns tokens. That is the main case for looking at Qwen 3.8 Max instead.
Well behind Claude Fable 5 on SWE-bench Pro (67.7 vs 80.0) and behind several Anthropic models on text rankings. No independent third-party benchmarks at GA — early claims are largely Alibaba-reported. Avoid it if you need independently verified benchmarks or Western data residency. Against Kimi K3 specifically, the gap shows up most on coding (96 vs 93).
Take a moderate workload of 10M input and 2M output tokens a month. Kimi K3 runs $60.00 (at $3/1M in and $15/1M out); Qwen 3.8 Max runs $32.00 (at $2/1M in and $6/1M out). That is a $28.00/month difference — Qwen 3.8 Max is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is Kimi K3 for frontier-level reasoning and agentic coding, with Qwen 3.8 Max handling multimodal and vision-heavy workloads at scale. Routing high-volume, low-stakes calls to Qwen 3.8 Max at $2/1M and reserving Kimi K3 for the hard cases is usually the cheapest arrangement that does not cost you quality.