Kimi K3 vs Qwen3.8 Max Preview vs GPT-5.4
Qwen3.8 Max Preview comes out ahead, 47 to 43 and 43 on our weighted score, and it is the cheaper option too.
Moonshot AIKimi K3
43/100- ECI157.6
- Price$3.00 / $15.00
- Context1.05M
- Our pick
Alibaba (Qwen)Qwen3.8 Max Preview
47/100- ECI—
- Price$2.00 / $6.00
- Context1M
OpenAIGPT-5.4
43/100- ECI156.9
- Price$2.50 / $15.00
- Context1.05M
Qwen3.8 Max Preview is our pick
Qwen3.8 Max Preview is the better all-round choice, scoring 47/100 against GPT-5.4 (43) and Kimi K3 (43). It leads on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3.8 Max PreviewQwen3.8 Max Preview $3.00 · GPT-5.4 $5.63 · Kimi K3 $6.00 per 1M tokens (3:1 blend)
- Longest contextGPT-5.4 and Kimi K3GPT-5.4 1,050,000 · Kimi K3 1,048,576 · Qwen3.8 Max Preview 1,000,000 tokens
- Widest inputsSame inputsKimi K3: Text, Images, Video · Qwen3.8 Max Preview: Text, Images, Video · GPT-5.4: Text, Images, PDFs
- Self-hostingKimi K3Publishes downloadable weights
| Measure | Weight | Kimi K3 | Qwen3.8 Max Preview | GPT-5.4 |
|---|---|---|---|---|
| Price | 50% | 13 | 27 | 14 |
| Inputs & features | 30% | 80 | 70 | 80 |
| Context window | 20% | 61 | 60 | 61 |
| Overall | 100% | 43/100 | 47/100 | 43/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Kimi K3Moonshot AI | Qwen3.8 Max PreviewAlibaba (Qwen) | GPT-5.4OpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 157.6 (best) | — | 156.9 |
| ECI rank | #13 of 148 (best) | — | #16 of 148 |
| GPQA DiamondGraduate-level science questions | 93.1% | — | 93.3% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 72.2% | — | 78.6% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 97.2% | — | 97.8% (best) |
| SWE-bench VerifiedFixing real GitHub issues | — | — | 76.9% |
| SimpleQA VerifiedShort factual questions | 50.6% (best) | — | 45.1% |
| Price per million tokens | |||
| Input | $3.00 | $2.00 (best) | $2.50 |
| Output | $15.00 | $6.00 (best) | $15.00 |
| Cached input | $0.30 | — | $0.25 (best) |
| Blended (3:1) | $6.00 | $3.00 (best) | $5.63 |
| Long-context rate | Same rate | Same rate | Over 272K: $5.00 / $22.50 |
| Price source | Official Moonshot AI API | Median of 6 providers | Official OpenAI API |
| Limits | |||
| Context window | 1,048,576 tokens | 1,000,000 tokens | 1,050,000 tokens (best) |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | Yes | Yes | No |
| Reasoning | Yeslow · high · max | Yes | Yeslow · medium · high · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | kimi-k3 | — | gpt-5.4 |
| API providers | 68 (best) | 6 | 36 |
| Released | Jul 16, 2026 | Jul 19, 2026 | Mar 5, 2026 |
| Knowledge cutoff | — | — | Aug 31, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Kimi K3$60.00
- Qwen3.8 Max Preview$32.00
- GPT-5.4$55.00
Which should you choose?
Which is better: Kimi K3, Qwen3.8 Max Preview or GPT-5.4?
Qwen3.8 Max Preview is the better all-round choice, scoring 47/100 against GPT-5.4 (43) and Kimi K3 (43). It leads on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Kimi K3, Qwen3.8 Max Preview or GPT-5.4?
Qwen3.8 Max Preview is cheaper at $2.00 input / $6.00 output per million tokens (median across 6 API providers). GPT-5.4 costs $2.50 input / $15.00 output per million tokens (official OpenAI API price); Kimi K3 costs $3.00 input / $15.00 output per million tokens (official Moonshot AI API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Qwen3.8 Max Preview versus $5.63 for GPT-5.4 (1.9× as much) and $6.00 for Kimi K3 (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Kimi K3 has an ECI of 157.6, Qwen3.8 Max Preview has not been scored yet and GPT-5.4 has an ECI of 156.9.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K3 and Qwen3.8 Max Preview yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-5.4 and Kimi K3 have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for Qwen3.8 Max Preview. Maximum output per response: Kimi K3 up to 131,072, Qwen3.8 Max Preview up to 131,072, GPT-5.4 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Kimi K3 accepts text, images and video; Qwen3.8 Max Preview accepts text, images and video; GPT-5.4 accepts text, images and PDFs. They handle the same number of input types.
Are any of these open source?
Kimi K3 publishes its weights and can be self-hosted; Qwen3.8 Max Preview and GPT-5.4 is proprietary.
Which is newer?
Qwen3.8 Max Preview is the newest, released Jul 19, 2026. Kimi K3 came out Jul 16, 2026; GPT-5.4 came out Mar 5, 2026. Knowledge cutoff: GPT-5.4 Aug 31, 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
