Model Comparison

DeepSeek-V2.5 vs Jamba 1.5 Mini

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is 1.4x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V2.5 outperforms in 3 benchmarks (Arena Hard, GSM8k, MMLU), while Jamba 1.5 Mini is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Wed Apr 01 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V2.5 costs less

For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 1.4x cheaper than Jamba 1.5 Mini ($0.20/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 1.4x cheaper than Jamba 1.5 Mini ($0.40/1M tokens).

In conclusion, Jamba 1.5 Mini is more expensive than DeepSeek-V2.5.*

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

Lowest available price from all providers
Wed Apr 01 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
AI21 Labs
Jamba 1.5 Mini
Input tokens$0.20
Output tokens$0.40
Best providerAWS Bedrock
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

184.0B diff

DeepSeek-V2.5 has 184.0B more parameters than Jamba 1.5 Mini, making it 353.8% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
AI21 Labs
Jamba 1.5 Mini
52.0Bparameters
236.0B
DeepSeek-V2.5
52.0B
Jamba 1.5 Mini

Context Window

Maximum input and output token capacity

Jamba 1.5 Mini accepts 256,144 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
AI21 Labs
Jamba 1.5 Mini
Input256,144 tokens
Output256,144 tokens
Wed Apr 01 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Jamba 1.5 Mini uses Jamba Open Model License.

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

DeepSeek-V2.5

deepseek

Open weights

Jamba 1.5 Mini

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Jamba 1.5 Mini was released on 2024-08-22.

Jamba 1.5 Mini is 4 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

1.9 years ago

Jamba 1.5 Mini

Aug 22, 2024

1.6 years ago

3mo newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while DeepSeek-V2.5's cutoff date is not specified.

We can confirm Jamba 1.5 Mini's training data extends to 2024-03-05, but cannot make a direct comparison without DeepSeek-V2.5's cutoff date.

DeepSeek-V2.5

—

Jamba 1.5 Mini

Mar 2024

Provider Availability

DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Jamba 1.5 Mini is available from Bedrock, Google.

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

Jamba 1.5 Mini

bedrock logo
AWS Bedrock
Input Price:Input: $0.20/1MOutput Price:Output: $0.40/1M
google logo
Google
Input Price:Input: $0.20/1MOutput Price:Output: $0.40/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Higher Arena Hard score (76.2% vs 46.1%)
Higher GSM8k score (95.1% vs 75.8%)
Higher MMLU score (80.4% vs 69.7%)
AI21 Labs
Larger context window (256,144 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
AI21 Labs
Jamba 1.5 Mini

FAQ

Common questions about DeepSeek-V2.5 vs Jamba 1.5 Mini

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is made by DeepSeek and Jamba 1.5 Mini is made by AI21 Labs. 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%. Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%.
DeepSeek-V2.5 is 1.4x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. Jamba 1.5 Mini costs $0.20/M input and $0.40/M output via bedrock.
DeepSeek-V2.5 supports 8K tokens and Jamba 1.5 Mini supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (8K vs 256K), input pricing ($0.14 vs $0.20/M), licensing (deepseek vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V2.5 is developed by DeepSeek and Jamba 1.5 Mini is developed by AI21 Labs.