Kimi K3 vs Command A Plus vs GPT-5.4
Too close to call on our weighted score (GPT-5.4 43, Kimi K3 43, Command A Plus 35). The right pick depends on what you value most.
Moonshot AIKimi K3
43/100- ECI157.6
- Price$3.00 / $15.00
- Context1.05M
CohereCommand A Plus
35/100- ECI—
- Price$2.50 / $10.00
- Context128K
OpenAIGPT-5.4
43/100- ECI156.9
- Price$2.50 / $15.00
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (GPT-5.4 43/100, Kimi K3 43/100, Command A Plus 35/100), so choose by what matters most for your work: Command A Plus 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 priceCommand A PlusCommand A Plus $4.38 · 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 · Command A Plus 128,000 tokens
- Widest inputsKimi K3 and GPT-5.4Kimi K3: Text, Images, Video · Command A Plus: Text, Images · GPT-5.4: Text, Images, PDFs
- Self-hostingKimi K3 and Command A PlusPublishes downloadable weights
| Measure | Weight | Kimi K3 | Command A Plus | GPT-5.4 |
|---|---|---|---|---|
| Price | 50% | 13 | 19 | 14 |
| Inputs & features | 30% | 80 | 70 | 80 |
| Context window | 20% | 61 | 24 | 61 |
| Overall | 100% | 43/100 | 35/100 | 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 | Command A PlusCohere | 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 | $2.50 (best) | $2.50 (best) |
| Output | $15.00 | $10.00 (best) | $15.00 |
| Cached input | $0.30 | — | $0.25 (best) |
| Blended (3:1) | $6.00 | $4.38 (best) | $5.63 |
| Long-context rate | Same rate | Same rate | Over 272K: $5.00 / $22.50 |
| Price source | Official Moonshot AI API | Official Cohere API | Official OpenAI API |
| Limits | |||
| Context window | 1,048,576 tokens | 128,000 tokens | 1,050,000 tokens (best) |
| Max output | 131,072 tokens (best) | 64,000 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yeslow · high · max | Yes | Yeslow · medium · high · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | kimi-k3 | command-a-plus-05-2026 | gpt-5.4 |
| API providers | 68 (best) | 1 | 36 |
| Released | Jul 16, 2026 | May 20, 2026 | Mar 5, 2026 |
| Knowledge cutoff | — | Apr 1, 2025 | 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
- Command A Plus$45.00
- GPT-5.4$55.00
Which should you choose?
Which is better: Kimi K3, Command A Plus or GPT-5.4?
It is close. Our weighted score puts them within a point (GPT-5.4 43/100, Kimi K3 43/100, Command A Plus 35/100), so choose by what matters most for your work: Command A Plus 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, Command A Plus or GPT-5.4?
Command A Plus is cheaper at $2.50 input / $10.00 output per million tokens (official Cohere API price). 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 $4.38 per million tokens for Command A Plus versus $5.63 for GPT-5.4 (1.3× as much) and $6.00 for Kimi K3 (1.4× 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, Command A Plus 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 Command A Plus 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 128,000 for Command A Plus. Maximum output per response: Kimi K3 up to 131,072, Command A Plus up to 64,000, GPT-5.4 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Kimi K3 accepts text, images and video; Command A Plus accepts text and images; GPT-5.4 accepts text, images and PDFs. Kimi K3 handles the widest range of inputs.
Are any of these open source?
Kimi K3 and Command A Plus publishes its weights and can be self-hosted; GPT-5.4 is proprietary.
Which is newer?
Kimi K3 is the newest, released Jul 16, 2026. Command A Plus came out May 20, 2026; GPT-5.4 came out Mar 5, 2026. Knowledge cutoff: Command A Plus Apr 1, 2025, 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.
