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Inkling-Small vs Mistral Large 4

Mistral Large 4 leads the LLM Stats Score 46.2 to 38.1. Inkling-Small is 2.0x cheaper per token.

Thinking Machines Lab · Mistral AI · Updated for 2026

Which is better?

Mistral Large 4 leads the overall LLM Stats Score 46.2 to 38.1, ranking #34 overall.

In the 2 individual benchmarks reported for both models, Mistral Large 4 wins 2; this is a narrower head-to-head signal than the composite indexes.

On price, Inkling-Small is roughly 2.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Mistral Large 4 also accepts a larger context window (1,000,000 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

  • cost matters — it's about 2.0x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose Mistral Large 4

  • overall performance matters — it scores 46.2 and ranks #34 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Inkling-Small
Thinking Machines Lab
Mistral Large 4
Mistral AI
Core performance indexes
LLM Stats Score
38.1
#77
46.2
#34
Reasoning
37.7
#77
44.0
#43
Coding
28.5
#67
35.8
#27
Agents
22.7
#70
34.3
#26
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
$0.30 / M
$0.68 / M
Output price
$1.20 / M
$2.09 / M
Context window
256,000
1,000,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Inkling-Small
Mistral Large 4
Vision
20.1#80
1.1#187
Tool use
19.0#70
27.1#26
Multimodal
17.4#86
1.7#160
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

24 reported for Inkling-Small · 18 for Mistral Large 4

2 shared

Inkling-Small outperforms in 0 benchmarks, while Mistral Large 4 is better at 2 benchmarks (AA-Briefcase, SciCode).

Mistral Large 4 significantly outperforms across most benchmarks.

Thu Oct 08 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 2.3x cheaper than Mistral Large 4 ($0.68/1M tokens).

For output processing, Inkling-Small ($1.20/1M tokens) is 1.7x cheaper than Mistral Large 4 ($2.09/1M tokens).

In conclusion, Mistral Large 4 is more expensive than Inkling-Small.*

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

Lowest available price from all providers
Thu Oct 08 2026 • llm-stats.com
Thinking Machines Lab
Inkling-Small
Input tokens$0.30
Output tokens$1.20
Best providerUnknown Organization
Mistral AI
Mistral Large 4
Input tokens$0.68
Output tokens$2.09
Best providerMistral
Notice missing or incorrect data?

Model Size

Parameter count comparison

774.0B diff

Mistral Large 4 has 774.0B more parameters than Inkling-Small, making it 280.4% larger.

Thinking Machines Lab
Inkling-Small
276.0Bparameters
Mistral AI
Mistral Large 4
1.1Tparameters
276.0B
Inkling-Small
1050.0B
Mistral Large 4

Context Window

Maximum input and output token capacity

Mistral Large 4 accepts 1,000,000 input tokens compared to Inkling-Small's 256,000 tokens. Only Inkling-Small specifies output context (256,000 tokens).

Thinking Machines Lab
Inkling-Small
Input256,000 tokens
Output256,000 tokens
Mistral AI
Mistral Large 4
Input1,000,000 tokens
Output- tokens
Thu Oct 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Inkling-Small and Mistral Large 4 support multimodal inputs.

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

Inkling-Small

Text
Images
Audio
Video

Mistral Large 4

Text
Images
Audio
Video

License

Usage and distribution terms

Inkling-Small is licensed under Apache 2.0, while Mistral Large 4 uses a proprietary license.

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

Inkling-Small

Apache 2.0

Open weights

Mistral Large 4

Proprietary

Closed source

Release Timeline

When each model was launched

Inkling-Small was released on 2026-07-30, while Mistral Large 4 was released on 2026-10-06.

Mistral Large 4 is 2 months newer than Inkling-Small.

Inkling-Small

Jul 30, 2026

2 months ago

Mistral Large 4

Oct 6, 2026

2 days ago

2mo newer

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, DeepInfra. Mistral Large 4 is available from Mistral AI.

Inkling-Small

thinking-machines logo
Unknown Organization
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.45/1MOutput Price:Output: $1.20/1M

Mistral Large 4

mistral logo
Mistral
Input Price:Input: $0.68/1MOutput Price:Output: $2.09/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Inkling-Small and Mistral Large 4 side-by-side, then vote on the output you prefer.

Inkling-Small
✓ Preferred
Mistral Large 4
Open in Playground

FAQ

Common questions about Inkling-Small vs Mistral Large 4.

Which is better, Inkling-Small or Mistral Large 4?

Mistral Large 4 leads the LLM Stats Score 46.2 to 38.1. Inkling-Small is made by Thinking Machines Lab and Mistral Large 4 is made by Mistral 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 Mistral Large 4 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%. Mistral Large 4 scores B3 AI Security Benchmark: 93.3%, CyBench: 93.0%, SciCode: 91.8%, KORABench: 84.5%, CyberGym: 82.0%.

Is Inkling-Small cheaper than Mistral Large 4?

Inkling-Small is 2.3x cheaper for input tokens. Inkling-Small costs $0.30/M input and $1.20/M output via thinking-machines. Mistral Large 4 costs $0.68/M input and $2.09/M output via mistral.

What are the context window sizes for Inkling-Small and Mistral Large 4?

Inkling-Small supports 256K tokens and Mistral Large 4 supports 1.0M 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 Mistral Large 4?

Key differences include LLM Stats Score (38.1 vs 46.2), context window (256K vs 1.0M), input pricing ($0.30 vs $0.68/M), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Inkling-Small and Mistral Large 4?

Inkling-Small is developed by Thinking Machines Lab and Mistral Large 4 is developed by Mistral AI.

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