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Inkling-Small vs Kimi K2.7 Code

Inkling-Small and Kimi K2.7 Code are closely matched at 39.3 and 39.6 on the LLM Stats Score. Inkling-Small is 2.7x cheaper per token.

Thinking Machines Lab · Moonshot AI · Updated for 2026

Which is better?

Inkling-Small and Kimi K2.7 Code are closely matched on the overall LLM Stats Score at 39.3 and 39.6.

In the 1 individual benchmarks reported for both models, Inkling-Small wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, Inkling-Small is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Kimi K2.7 Code also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Inkling-Small

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • cost matters — it's about 2.7x cheaper per token
  • you want the most recent training data — it shipped Jul 2026

Choose Kimi K2.7 Code

  • you process long inputs — it offers a 262,144 token context window

At a glance

The differences that matter most.

Inkling-Small
Thinking Machines Lab
Kimi K2.7 Code
Moonshot AI
Core performance indexes
LLM Stats Score
39.3
#53
39.6
#49
Reasoning
39.0
#52
35.2
#74
Coding
31.1
#45
32.2
#42
Agents
24.8
#45
28.0
#37
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.30 / M
$0.74 / M
Output price
$1.20 / M
$3.50 / M
Context window
256,000
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Inkling-Small
Kimi K2.7 Code
Tool use
23.3#38
25.6#26
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

24 reported for Inkling-Small · 9 for Kimi K2.7 Code

1 shared

Inkling-Small outperforms in 1 benchmarks (MCP Atlas), while Kimi K2.7 Code is better at 0 benchmarks.

Inkling-Small significantly outperforms across most benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Inkling-Small costs less

For input processing, Inkling-Small ($0.30/1M tokens) is 2.5x cheaper than Kimi K2.7 Code ($0.74/1M tokens).

For output processing, Inkling-Small ($1.20/1M tokens) is 2.9x cheaper than Kimi K2.7 Code ($3.50/1M tokens).

In conclusion, Kimi K2.7 Code is more expensive than Inkling-Small.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Aug 28 2026 • llm-stats.com
Thinking Machines Lab
Inkling-Small
Input tokens$0.30
Output tokens$1.20
Best providerUnknown Organization
Moonshot AI
Kimi K2.7 Code
Input tokens$0.74
Output tokens$3.50
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

724.0B diff

Kimi K2.7 Code has 724.0B more parameters than Inkling-Small, making it 262.3% larger.

Thinking Machines Lab
Inkling-Small
276.0Bparameters
Moonshot AI
Kimi K2.7 Code
1.0Tparameters
276.0B
Inkling-Small
1000.0B
Kimi K2.7 Code

Context Window

Maximum input and output token capacity

Kimi K2.7 Code accepts 262,144 input tokens compared to Inkling-Small's 256,000 tokens. Inkling-Small can generate longer responses up to 256,000 tokens, while Kimi K2.7 Code is limited to 131,072 tokens.

Thinking Machines Lab
Inkling-Small
Input256,000 tokens
Output256,000 tokens
Moonshot AI
Kimi K2.7 Code
Input262,144 tokens
Output131,072 tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Inkling-Small and Kimi K2.7 Code support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Inkling-Small

Text
Images
Audio
Video

Kimi K2.7 Code

Text
Images
Audio
Video

License

Usage and distribution terms

Inkling-Small is licensed under Apache 2.0, while Kimi K2.7 Code uses Modified MIT License.

License differences may affect how you can use these models in commercial or open-source projects.

Inkling-Small

Apache 2.0

Open weights

Kimi K2.7 Code

Modified MIT License

Open weights

Release Timeline

When each model was launched

Inkling-Small was released on 2026-07-30, while Kimi K2.7 Code was released on 2026-06-12.

Inkling-Small is 2 months newer than Kimi K2.7 Code.

Inkling-Small

Jul 30, 2026

4 weeks ago

1mo newer
Kimi K2.7 Code

Jun 12, 2026

2 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Inkling-Small is available from Thinking Machines Lab. Kimi K2.7 Code is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.

Inkling-Small

thinking-machines logo
Unknown Organization
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Kimi K2.7 Code

deepinfra logo
Deepinfra
Input Price:Input: $0.74/1MOutput Price:Output: $3.50/1M
fireworks logo
Fireworks
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
moonshot logo
Unknown Organization
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
novita logo
Novita
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
together logo
Together
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Inkling-Small and Kimi K2.7 Code side-by-side, then vote on the output you prefer.

Inkling-Small
✓ Preferred
Kimi K2.7 Code
Open in Playground

FAQ

Common questions about Inkling-Small vs Kimi K2.7 Code.

Which is better, Inkling-Small or Kimi K2.7 Code?

Inkling-Small and Kimi K2.7 Code are closely matched on the LLM Stats Score at 39.3 and 39.6. Inkling-Small is made by Thinking Machines Lab and Kimi K2.7 Code is made by Moonshot AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Inkling-Small compare to Kimi K2.7 Code in benchmarks?

Inkling-Small scores AIME 2026: 95.5%, VoiceBench Avg: 90.1%, GPQA: 89.5%, Global-MMLU-Lite: 86.7%, ARC-AGI: 84.0%. Kimi K2.7 Code scores MCP-Mark: 81.1%, MCP Atlas: 76.0%, LiveBench: 71.9%, Kimi Code Bench v2: 62.0%, Program Bench: 53.6%.

Is Inkling-Small cheaper than Kimi K2.7 Code?

Inkling-Small is 2.5x cheaper for input tokens. Inkling-Small costs $0.30/M input and $1.20/M output via thinking-machines. Kimi K2.7 Code costs $0.74/M input and $3.50/M output via deepinfra.

What are the context window sizes for Inkling-Small and Kimi K2.7 Code?

Inkling-Small supports 256K tokens and Kimi K2.7 Code supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Inkling-Small and Kimi K2.7 Code?

Key differences include LLM Stats Score (39.3 vs 39.6), context window (256K vs 262K), input pricing ($0.30 vs $0.74/M), licensing (Apache 2.0 vs Modified MIT License). See the full comparison above for benchmark-by-benchmark results.

Who makes Inkling-Small and Kimi K2.7 Code?

Inkling-Small is developed by Thinking Machines Lab and Kimi K2.7 Code is developed by Moonshot AI.

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