Inkling vs Mistral Large 4 vs Kimi K2.7 Code
Mistral Large 4 comes out ahead, 67 to 63 and 63 on our weighted score, and it is the cheaper option too.
Thinking MachinesInkling
63/100- ECI148.5
- Price$1.00 / $4.05
- Context1.05M
- Our pick
Mistral AIMistral Large 4
67/100- ECI150.6
- Price$0.70 / $2.10
- Context1.05M
Moonshot AIKimi K2.7 Code
63/100- ECI150.2
- Price$0.95 / $4.00
- Context262K
Mistral Large 4 is our pick
Mistral Large 4 is the better all-round choice, scoring 67/100 against Kimi K2.7 Code (63) and Inkling (63). It leads on price. Kimi K2.7 Code wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 4Capabilities Index (ECI): Mistral Large 4 150.6 · Kimi K2.7 Code 150.2 · Inkling 148.5
- Lowest priceMistral Large 4Mistral Large 4 $1.05 · Kimi K2.7 Code $1.71 · Inkling $1.76 per 1M tokens (3:1 blend)
- Longest contextInkling and Mistral Large 4Inkling 1,048,576 · Mistral Large 4 1,048,576 · Kimi K2.7 Code 262,144 tokens
- Widest inputsInkling and Kimi K2.7 CodeInkling: Text, Images, Audio · Mistral Large 4: Text, Images · Kimi K2.7 Code: Text, Images, Video
- Self-hostingInkling and Kimi K2.7 CodePublishes downloadable weights (Apache-2.0)
| Measure | Weight | Inkling | Mistral Large 4 | Kimi K2.7 Code |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 75 | 77 | 77 |
| Price | 25% | 37 | 47 | 37 |
| Inputs & features | 15% | 70 | 70 | 80 |
| Context window | 10% | 61 | 61 | 37 |
| Overall | 100% | 63/100 | 67/100 | 63/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | InklingThinking Machines | Mistral Large 4Mistral AI | Kimi K2.7 CodeMoonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 148.5 | 150.6 (best) | 150.2 |
| ECI rank | #67 of 165 | #57 of 165 (best) | #59 of 165 |
| GPQA DiamondGraduate-level science questions | 88.3% (best) | 88.1% | 87.9% |
| FrontierMath Tiers 1–3Research-level mathematics | 33.3% | 58.6% (best) | 54.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 88.9% | 98.3% (best) | 95.6% |
| SimpleQA VerifiedShort factual questions | 40.3% (best) | 20.0% | 36.5% |
| Price per million tokens | |||
| Input | $1.00 | $0.70 (best) | $0.95 |
| Output | $4.05 | $2.10 (best) | $4.00 |
| Cached input | $0.17 | $0.07 (best) | $0.19 |
| Blended (3:1) | $1.76 | $1.05 (best) | $1.71 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Thinking Machines API | Official Mistral API | Official Moonshot AI API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,048,576 tokens (best) | 262,144 tokens |
| Max output | 1,048,576 tokens (best) | 262,144 tokens | 262,144 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh · max | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Open |
| API model ID | thinkingmachines/Inkling:peft:262144:sampling-nvfp4 | mistral-large-4 | kimi-k2.7-code |
| API providers | 20 | 15 | 49 (best) |
| Released | Jul 15, 2026 | Oct 6, 2026 | Jun 12, 2026 |
| Knowledge cutoff | — | — | 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.
- Inkling$18.10
- Mistral Large 4$11.20
- Kimi K2.7 Code$17.50
Which should you choose?
Which is better: Inkling, Mistral Large 4 or Kimi K2.7 Code?
Mistral Large 4 is the better all-round choice, scoring 67/100 against Kimi K2.7 Code (63) and Inkling (63). It leads on price. Kimi K2.7 Code wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Inkling, Mistral Large 4 or Kimi K2.7 Code?
Mistral Large 4 is cheaper at $0.70 input / $2.10 output per million tokens (official Mistral API price). Kimi K2.7 Code costs $0.95 input / $4.00 output per million tokens (official Moonshot AI API price); Inkling costs $1.00 input / $4.05 output per million tokens (official Thinking Machines API price). At a typical mix of three input tokens to one output token, that is $1.05 per million tokens for Mistral Large 4 versus $1.71 for Kimi K2.7 Code (1.6× as much) and $1.76 for Inkling (1.7× as much).
Which scores higher on benchmarks?
Mistral Large 4 scores higher on the Capabilities Index (ECI): Mistral Large 4 150.6 (#57 of 165), Kimi K2.7 Code 150.2 (#59 of 165) and Inkling 148.5 (#67 of 165). The confidence ranges of the top two overlap (147.4–153.5 vs 148.1–151.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — Inkling 88.3%, Mistral Large 4 88.1%, Kimi K2.7 Code 87.9%; FrontierMath Tiers 1–3 — Mistral Large 4 58.6%, Kimi K2.7 Code 54.0%, Inkling 33.3%; OTIS Mock AIME 2024–2025 — Mistral Large 4 98.3%, Kimi K2.7 Code 95.6%, Inkling 88.9%; SimpleQA Verified — Inkling 40.3%, Kimi K2.7 Code 36.5%, Mistral Large 4 20.0%.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling, Mistral Large 4 and Kimi K2.7 Code yet, so there is no like-for-like coding score. On overall capability, Mistral Large 4 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Inkling and Mistral Large 4 have the largest context windows (1,048,576 and 1,048,576 tokens), against 262,144 for Kimi K2.7 Code. Maximum output per response: Inkling up to 1,048,576, Mistral Large 4 up to 262,144, Kimi K2.7 Code up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Inkling accepts text, images and audio; Mistral Large 4 accepts text and images; Kimi K2.7 Code accepts text, images and video. Inkling handles the widest range of inputs.
Are any of these open source?
Inkling and Kimi K2.7 Code publishes its weights (Apache-2.0) and can be self-hosted; Mistral Large 4 is proprietary.
Which is newer?
Mistral Large 4 is the newest, released Oct 6, 2026. Inkling came out Jul 15, 2026; Kimi K2.7 Code came out Jun 12, 2026. Knowledge cutoff: Kimi K2.7 Code 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 Nov 2, 2026.
