Model Comparison

DeepSeek-V2.5 vs Gemma 3 1B

DeepSeek-V2.5 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V2.5 outperforms in 3 benchmarks (GSM8k, HumanEval, MATH), while Gemma 3 1B is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Fri May 01 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Fri May 01 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Google
Gemma 3 1B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

235.0B diff

DeepSeek-V2.5 has 235.0B more parameters than Gemma 3 1B, making it 23500.0% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Google
Gemma 3 1B
1.0Bparameters
236.0B
DeepSeek-V2.5
1.0B
Gemma 3 1B

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Google
Gemma 3 1B
Input- tokens
Output- tokens
Fri May 01 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Gemma 3 1B uses Gemma.

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

DeepSeek-V2.5

deepseek

Open weights

Gemma 3 1B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Gemma 3 1B was released on 2025-03-12.

Gemma 3 1B is 10 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.0 years ago

Gemma 3 1B

Mar 12, 2025

1.1 years ago

10mo 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

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (8,192 tokens)
Higher GSM8k score (95.1% vs 62.8%)
Higher HumanEval score (89.0% vs 41.5%)
Higher MATH score (74.7% vs 48.0%)
Google

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Google
Gemma 3 1B

FAQ

Common questions about DeepSeek-V2.5 vs Gemma 3 1B

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is made by DeepSeek and Gemma 3 1B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Gemma 3 1B scores IFEval: 80.2%, GSM8k: 62.8%, Natural2Code: 56.0%, MATH: 48.0%, HumanEval: 41.5%.
DeepSeek-V2.5 supports 8K tokens and Gemma 3 1B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (deepseek vs Gemma). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V2.5 is developed by DeepSeek and Gemma 3 1B is developed by Google.