Model Comparison

DeepSeek-R1 vs Jamba 1.5 Mini

Comparing DeepSeek-R1 and Jamba 1.5 Mini across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Jamba 1.5 Mini don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Jamba 1.5 Mini costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 2.8x more expensive than Jamba 1.5 Mini ($0.20/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 5.5x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).

In conclusion, DeepSeek-R1 is more expensive than Jamba 1.5 Mini.*

* 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-R1
Input tokens$0.55
Output tokens$2.19
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

619.0B diff

DeepSeek-R1 has 619.0B more parameters than Jamba 1.5 Mini, making it 1190.4% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
AI21 Labs
Jamba 1.5 Mini
52.0Bparameters
671.0B
DeepSeek-R1
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-R1's 131,072 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while DeepSeek-R1 is limited to 131,072 tokens.

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 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-R1 is licensed under MIT, 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-R1

MIT

Open weights

Jamba 1.5 Mini

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Jamba 1.5 Mini was released on 2024-08-22.

DeepSeek-R1 is 5 months newer than Jamba 1.5 Mini.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

5mo newer
Jamba 1.5 Mini

Aug 22, 2024

1.6 years ago

Knowledge Cutoff

When training data ends

Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while DeepSeek-R1'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-R1's cutoff date.

DeepSeek-R1

—

Jamba 1.5 Mini

Mar 2024

Provider Availability

DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Jamba 1.5 Mini is available from Bedrock, Google.

DeepSeek-R1

deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M
together logo
Together
Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M
fireworks logo
Fireworks
Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

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
AI21 Labs
Larger context window (256,144 tokens)
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
AI21 Labs
Jamba 1.5 Mini

FAQ

Common questions about DeepSeek-R1 vs Jamba 1.5 Mini

DeepSeek-R1 (DeepSeek) and Jamba 1.5 Mini (AI21 Labs) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%.
Jamba 1.5 Mini is 2.8x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. Jamba 1.5 Mini costs $0.20/M input and $0.40/M output via bedrock.
DeepSeek-R1 supports 131K 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 (131K vs 256K), input pricing ($0.55 vs $0.20/M), licensing (MIT vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1 is developed by DeepSeek and Jamba 1.5 Mini is developed by AI21 Labs.