Model Comparison

DeepSeek VL2 Tiny vs Jamba 1.5 Large

Comparing DeepSeek VL2 Tiny and Jamba 1.5 Large across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 Tiny and Jamba 1.5 Large don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

395.0B diff

Jamba 1.5 Large has 395.0B more parameters than DeepSeek VL2 Tiny, making it 13166.7% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
AI21 Labs
Jamba 1.5 Large
398.0Bparameters
3.0B
DeepSeek VL2 Tiny
398.0B
Jamba 1.5 Large

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Large specifies input context (256,000 tokens). Only Jamba 1.5 Large specifies output context (256,000 tokens).

DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
Tue May 12 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Tiny supports multimodal inputs, whereas Jamba 1.5 Large 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

Jamba 1.5 Large

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny is licensed under deepseek, while Jamba 1.5 Large uses Jamba Open Model License.

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

DeepSeek VL2 Tiny

deepseek

Open weights

Jamba 1.5 Large

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while Jamba 1.5 Large was released on 2024-08-22.

DeepSeek VL2 Tiny is 4 months newer than Jamba 1.5 Large.

DeepSeek VL2 Tiny

Dec 13, 2024

1.4 years ago

3mo newer
Jamba 1.5 Large

Aug 22, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while DeepSeek VL2 Tiny's cutoff date is not specified.

We can confirm Jamba 1.5 Large's training data extends to 2024-03-05, but cannot make a direct comparison without DeepSeek VL2 Tiny's cutoff date.

DeepSeek VL2 Tiny

—

Jamba 1.5 Large

Mar 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Supports multimodal inputs
AI21 Labs
Larger context window (256,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
AI21 Labs
Jamba 1.5 Large

FAQ

Common questions about DeepSeek VL2 Tiny vs Jamba 1.5 Large.

Which is better, DeepSeek VL2 Tiny or Jamba 1.5 Large?

DeepSeek VL2 Tiny (DeepSeek) and Jamba 1.5 Large (AI21 Labs) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek VL2 Tiny compare to Jamba 1.5 Large in benchmarks?

DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%.

What are the context window sizes for DeepSeek VL2 Tiny and Jamba 1.5 Large?

DeepSeek VL2 Tiny supports an unknown number of tokens and Jamba 1.5 Large supports 256K 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 Jamba 1.5 Large?

Key differences include multimodal support (yes vs no), licensing (deepseek vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 Tiny and Jamba 1.5 Large?

DeepSeek VL2 Tiny is developed by DeepSeek and Jamba 1.5 Large is developed by AI21 Labs.