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DeepSeek VL2 vs Mistral NeMo Instruct

DeepSeek VL2 leads the LLM Stats Score 2.9 to -4.8.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek VL2 leads the overall LLM Stats Score 2.9 to -4.8, ranking #311 overall.

Mistral NeMo Instruct also accepts a larger context window (131,072 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 DeepSeek VL2

  • overall performance matters — it scores 2.9 and ranks #311 on LLM Stats
  • you want the most recent training data — it shipped Dec 2024

Choose Mistral NeMo Instruct

  • you process long inputs — it offers a 131,072 token context window

At a glance

The differences that matter most.

DeepSeek VL2
DeepSeek
Mistral NeMo Instruct
Mistral AI
Core performance indexes
LLM Stats Score
2.9
#311
-4.8
#353
Reasoning
-1.9
#329
-5.0
#345
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.02 / M
Output price
— / M
$0.03 / M
Context window
129,280
131,072

Individual benchmarks

14 reported for DeepSeek VL2 · 8 for Mistral NeMo Instruct

No common benchmarks found

DeepSeek VL2 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

15.0B diff

DeepSeek VL2 has 15.0B more parameters than Mistral NeMo Instruct, making it 125.0% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
27.0B
DeepSeek VL2
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

Mistral NeMo Instruct accepts 131,072 input tokens compared to DeepSeek VL2's 129,280 tokens. Mistral NeMo Instruct can generate longer responses up to 131,072 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Mistral AI
Mistral NeMo Instruct
Input131,072 tokens
Output131,072 tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

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

DeepSeek VL2

Text
Images
Audio
Video

Mistral NeMo Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 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

deepseek

Open weights

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

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

DeepSeek VL2 is 5 months newer than Mistral NeMo Instruct.

DeepSeek VL2

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

Provider Availability

DeepSeek VL2 is available from Replicate. Mistral NeMo Instruct is available from DeepInfra, Google, Mistral AI.

DeepSeek VL2

replicate logo
Replicate

Mistral NeMo Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.02/1MOutput Price:Output: $0.03/1M
google logo
Google
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
mistral logo
Mistral
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
* 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 DeepSeek VL2 and Mistral NeMo Instruct side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Mistral NeMo Instruct
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs Mistral NeMo Instruct.

Which is better, DeepSeek VL2 or Mistral NeMo Instruct?

DeepSeek VL2 leads the LLM Stats Score 2.9 to -4.8. DeepSeek VL2 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 compare to Mistral NeMo Instruct in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. 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 and Mistral NeMo Instruct?

DeepSeek VL2 supports 129K 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 and Mistral NeMo Instruct?

Key differences include LLM Stats Score (2.9 vs -4.8), context window (129K vs 131K), 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 and Mistral NeMo Instruct?

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

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