MAI-Code-1-Flash vs Kimi K2.7 Code Highspeed vs Nex-N2-Pro
Kimi K2.7 Code Highspeed comes out ahead, 63 to 57 and 41 on our weighted score, though Nex-N2-Pro is 3.4× cheaper per token.
MicrosoftMAI-Code-1-Flash
41/100- ECI—
- Price—
- Context256K
- Our pick
Moonshot AIKimi K2.7 Code Highspeed
63/100- ECI—
- Price$1.90 / $8.00
- Context262K
Nex AGI
Nex-N2-Pro
57/100- ECI—
- Price$0.50 / $2.50
- Context262K
Kimi K2.7 Code Highspeed is our pick
Kimi K2.7 Code Highspeed is the better all-round choice, scoring 63/100 against Nex-N2-Pro (57) and MAI-Code-1-Flash (41). It leads on inputs & features. The score weighs inputs & features 60%, context window 40%. 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 priceNex-N2-ProNex-N2-Pro $1.00 · Kimi K2.7 Code Highspeed $3.42 per 1M tokens (3:1 blend) · MAI-Code-1-Flash unpriced
- Longest contextKimi K2.7 Code Highspeed and Nex-N2-ProKimi K2.7 Code Highspeed 262,144 · Nex-N2-Pro 262,144 · MAI-Code-1-Flash 256,000 tokens
- Widest inputsKimi K2.7 Code HighspeedMAI-Code-1-Flash: Text · Kimi K2.7 Code Highspeed: Text, Images, Video · Nex-N2-Pro: Text, Images
- Self-hostingKimi K2.7 Code Highspeed and Nex-N2-ProPublishes downloadable weights
| Measure | Weight | MAI-Code-1-Flash | Kimi K2.7 Code Highspeed | Nex-N2-Pro |
|---|---|---|---|---|
| Inputs & features | 60% | 45 | 80 | 70 |
| Context window | 40% | 36 | 37 | 37 |
| Overall | 100% | 41/100 | 63/100 | 57/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | MAI-Code-1-FlashMicrosoft | Kimi K2.7 Code HighspeedMoonshot AI | Nex-N2-ProNex AGI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $1.90 | $0.50 (best) |
| Output | — | $8.00 | $2.50 (best) |
| Cached input | — | — | — |
| Blended (3:1) | — | $3.42 | $1.00 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 11 providers | Median of 1 providers |
| Limits | |||
| Context window | 256,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 128,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | — | — |
| API providers | — | 11 (best) | 1 |
| Released | Jun 2, 2026 | Jun 12, 2026 | Jun 2, 2026 |
| Knowledge cutoff | Dec 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.
- MAI-Code-1-Flash—
- Kimi K2.7 Code Highspeed$35.00
- Nex-N2-Pro$10.00
Which should you choose?
Which is better: MAI-Code-1-Flash, Kimi K2.7 Code Highspeed or Nex-N2-Pro?
Kimi K2.7 Code Highspeed is the better all-round choice, scoring 63/100 against Nex-N2-Pro (57) and MAI-Code-1-Flash (41). It leads on inputs & features. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, MAI-Code-1-Flash, Kimi K2.7 Code Highspeed or Nex-N2-Pro?
Nex-N2-Pro is cheaper at $0.50 input / $2.50 output per million tokens (median across 1 API provider). Kimi K2.7 Code Highspeed costs $1.90 input / $8.00 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for Nex-N2-Pro versus $3.42 for Kimi K2.7 Code Highspeed (3.4× as much). MAI-Code-1-Flash has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MAI-Code-1-Flash has not been scored yet, Kimi K2.7 Code Highspeed has not been scored yet and Nex-N2-Pro has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MAI-Code-1-Flash, Kimi K2.7 Code Highspeed and Nex-N2-Pro 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?
Kimi K2.7 Code Highspeed and Nex-N2-Pro have the largest context windows (262,144 and 262,144 tokens), against 256,000 for MAI-Code-1-Flash. Maximum output per response: MAI-Code-1-Flash up to 128,000, Kimi K2.7 Code Highspeed up to 262,144, Nex-N2-Pro up to 262,144 tokens.
Which can read images, PDFs, audio or video?
MAI-Code-1-Flash accepts text; Kimi K2.7 Code Highspeed accepts text, images and video; Nex-N2-Pro accepts text and images. Kimi K2.7 Code Highspeed handles the widest range of inputs.
Are any of these open source?
Kimi K2.7 Code Highspeed and Nex-N2-Pro publishes its weights and can be self-hosted; MAI-Code-1-Flash is proprietary.
Which is newer?
Kimi K2.7 Code Highspeed is the newest, released Jun 12, 2026. MAI-Code-1-Flash came out Jun 2, 2026; Nex-N2-Pro came out Jun 2, 2026. Knowledge cutoff: MAI-Code-1-Flash Dec 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.
