Command A Plus vs Pareto vs Kimi K2.7 Code Highspeed
Kimi K2.7 Code Highspeed comes out ahead, 44 to 35 and 34 on our weighted score, and it is the cheaper option too.
CohereCommand A Plus
35/100- ECI—
- Price$2.50 / $10.00
- Context128K
Unbiased
Pareto
34/100- ECI—
- Price$2.50 / $7.50
- Context262K
- Our pick
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
Kimi K2.7 Code Highspeed is our pick
Kimi K2.7 Code Highspeed is the better all-round choice, scoring 44/100 against Command A Plus (35) and Pareto (34). It leads on price and inputs & features. 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 priceKimi K2.7 Code HighspeedKimi K2.7 Code Highspeed $3.42 · Pareto $3.75 · Command A Plus $4.38 per 1M tokens (3:1 blend)
- Longest contextPareto and Kimi K2.7 Code HighspeedPareto 262,144 · Kimi K2.7 Code Highspeed 262,144 · Command A Plus 128,000 tokens
- Widest inputsKimi K2.7 Code HighspeedCommand A Plus: Text, Images · Pareto: Text, Images · Kimi K2.7 Code Highspeed: Text, Images, Video
- Self-hostingCommand A Plus and Kimi K2.7 Code HighspeedPublishes downloadable weights
| Measure | Weight | Command A Plus | Pareto | Kimi K2.7 Code Highspeed |
|---|---|---|---|---|
| Price | 50% | 19 | 23 | 25 |
| Inputs & features | 30% | 70 | 50 | 80 |
| Context window | 20% | 24 | 37 | 37 |
| Overall | 100% | 35/100 | 34/100 | 44/100 |
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 | Command A PlusCohere | ParetoUnbiased | Kimi K2.7 Code HighspeedMoonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.50 | $2.50 | $1.90 (best) |
| Output | $10.00 | $7.50 (best) | $8.00 |
| Cached input | — | — | — |
| Blended (3:1) | $4.38 | $3.75 | $3.42 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Cohere API | Median of 4 providers | Median of 11 providers |
| Limits | |||
| Context window | 128,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 64,000 tokens | 131,072 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | command-a-plus-05-2026 | — | — |
| API providers | 1 | 4 | 11 (best) |
| Released | May 20, 2026 | Sep 17, 2026 | Jun 12, 2026 |
| Knowledge cutoff | Apr 1, 2025 | — | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Command A Plus$45.00
- Pareto$40.00
- Kimi K2.7 Code Highspeed$35.00
Which should you choose?
Which is better: Command A Plus, Pareto or Kimi K2.7 Code Highspeed?
Kimi K2.7 Code Highspeed is the better all-round choice, scoring 44/100 against Command A Plus (35) and Pareto (34). It leads on price and inputs & features. 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, Command A Plus, Pareto or Kimi K2.7 Code Highspeed?
Kimi K2.7 Code Highspeed is cheaper at $1.90 input / $8.00 output per million tokens (median across 11 API providers). Pareto costs $2.50 input / $7.50 output per million tokens (median across 4 API providers); Command A Plus costs $2.50 input / $10.00 output per million tokens (official Cohere API price). At a typical mix of three input tokens to one output token, that is $3.42 per million tokens for Kimi K2.7 Code Highspeed versus $3.75 for Pareto (1.1× as much) and $4.38 for Command A Plus (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Command A Plus has not been scored yet, Pareto has not been scored yet and Kimi K2.7 Code Highspeed has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Command A Plus, Pareto and Kimi K2.7 Code Highspeed 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?
Pareto and Kimi K2.7 Code Highspeed have the largest context windows (262,144 and 262,144 tokens), against 128,000 for Command A Plus. Maximum output per response: Command A Plus up to 64,000, Pareto up to 131,072, Kimi K2.7 Code Highspeed up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Command A Plus accepts text and images; Pareto accepts text and images; Kimi K2.7 Code Highspeed accepts text, images and video. Kimi K2.7 Code Highspeed handles the widest range of inputs.
Are any of these open source?
Command A Plus and Kimi K2.7 Code Highspeed publishes its weights and can be self-hosted; Pareto is proprietary.
Which is newer?
Pareto is the newest, released Sep 17, 2026. Kimi K2.7 Code Highspeed came out Jun 12, 2026; Command A Plus came out May 20, 2026. Knowledge cutoff: Command A Plus Apr 1, 2025, Kimi K2.7 Code Highspeed Jan 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.
