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DeepSeek VL2 Tiny vs Mistral NeMo Instruct

DeepSeek VL2 Tiny and Mistral NeMo Instruct are closely matched at -4.7 and -4.8 on the LLM Stats Score.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek VL2 Tiny and Mistral NeMo Instruct are closely matched on the overall LLM Stats Score at -4.7 and -4.8.

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

Choose DeepSeek VL2 Tiny

  • you want the most recent training data — it shipped Dec 2024

Choose Mistral NeMo Instruct

  • you want predictable pricing at $0.02/M input and $0.03/M output

At a glance

The differences that matter most.

DeepSeek VL2 Tiny
DeepSeek
Mistral NeMo Instruct
Mistral AI
Core performance indexes
LLM Stats Score
-4.7
#357
-4.8
#359
Reasoning
-12.7
#368
-5.0
#351
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.02 / M
Output price
— / M
$0.03 / M
Context window
—
131,072

Individual benchmarks

14 reported for DeepSeek VL2 Tiny · 8 for Mistral NeMo Instruct

No common benchmarks found

DeepSeek VL2 Tiny and Mistral NeMo Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

9.0B diff

Mistral NeMo Instruct has 9.0B more parameters than DeepSeek VL2 Tiny, making it 300.0% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
3.0B
DeepSeek VL2 Tiny
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

Only Mistral NeMo Instruct specifies input context (131,072 tokens). Only Mistral NeMo Instruct specifies output context (131,072 tokens).

DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
Mistral AI
Mistral NeMo Instruct
Input131,072 tokens
Output131,072 tokens
Wed Sep 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek VL2 Tiny supports multimodal inputs, whereas Mistral NeMo Instruct does not.

DeepSeek VL2 Tiny can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2 Tiny

Text
Images
Audio
Video

Mistral NeMo Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny is licensed under deepseek, while Mistral NeMo Instruct uses Apache 2.0.

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

DeepSeek VL2 Tiny

deepseek

Open weights

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while Mistral NeMo Instruct was released on 2024-07-18.

DeepSeek VL2 Tiny is 5 months newer than Mistral NeMo Instruct.

DeepSeek VL2 Tiny

Dec 13, 2024

1.8 years ago

4mo newer
Mistral NeMo Instruct

Jul 18, 2024

2.2 years 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek VL2 Tiny and Mistral NeMo Instruct side-by-side, then vote on the output you prefer.

DeepSeek VL2 Tiny
✓ Preferred
Mistral NeMo Instruct
Open in Playground

FAQ

Common questions about DeepSeek VL2 Tiny vs Mistral NeMo Instruct.

Which is better, DeepSeek VL2 Tiny or Mistral NeMo Instruct?

DeepSeek VL2 Tiny and Mistral NeMo Instruct are closely matched on the LLM Stats Score at -4.7 and -4.8. DeepSeek VL2 Tiny is made by DeepSeek and Mistral NeMo Instruct 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 DeepSeek VL2 Tiny compare to Mistral NeMo Instruct in benchmarks?

DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.

What are the context window sizes for DeepSeek VL2 Tiny and Mistral NeMo Instruct?

DeepSeek VL2 Tiny supports an unknown number of tokens and Mistral NeMo Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek VL2 Tiny and Mistral NeMo Instruct?

Key differences include LLM Stats Score (-4.7 vs -4.8), multimodal support (yes vs no), licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 Tiny and Mistral NeMo Instruct?

DeepSeek VL2 Tiny is developed by DeepSeek and Mistral NeMo Instruct is developed by Mistral AI.

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