Model Comparison

GPT-4.1 nano vs Jamba 1.5 Mini

GPT-4.1 nano significantly outperforms across most benchmarks. GPT-4.1 nano is 1.4x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GPT-4.1 nano outperforms in 2 benchmarks (GPQA, MMLU), while Jamba 1.5 Mini is better at 0 benchmarks.

GPT-4.1 nano significantly outperforms across most benchmarks.

Mon Apr 20 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GPT-4.1 nano costs less

For input processing, GPT-4.1 nano ($0.10/1M tokens) is 2.0x cheaper than Jamba 1.5 Mini ($0.20/1M tokens).

For output processing, GPT-4.1 nano ($0.40/1M tokens) costs the same as Jamba 1.5 Mini ($0.40/1M tokens).

In conclusion, Jamba 1.5 Mini is more expensive than GPT-4.1 nano.*

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

Lowest available price from all providers
Mon Apr 20 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
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→

Context Window

Maximum input and output token capacity

GPT-4.1 nano accepts 1,047,576 input tokens compared to Jamba 1.5 Mini's 256,144 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while GPT-4.1 nano is limited to 32,768 tokens.

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
AI21 Labs
Jamba 1.5 Mini
Input256,144 tokens
Output256,144 tokens
Mon Apr 20 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4.1 nano supports multimodal inputs, whereas Jamba 1.5 Mini does not.

GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4.1 nano

Text
Images
Audio
Video

Jamba 1.5 Mini

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, 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.

GPT-4.1 nano

Proprietary

Closed source

Jamba 1.5 Mini

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while Jamba 1.5 Mini was released on 2024-08-22.

GPT-4.1 nano is 8 months newer than Jamba 1.5 Mini.

GPT-4.1 nano

Apr 14, 2025

1.0 years ago

7mo newer
Jamba 1.5 Mini

Aug 22, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a knowledge cutoff of 2024-05-31, while Jamba 1.5 Mini has a cutoff of 2024-03-05.

GPT-4.1 nano has more recent training data (up to 2024-05-31), making it potentially better informed about events through that date compared to Jamba 1.5 Mini (2024-03-05).

GPT-4.1 nano

May 2024

2 mo newer
Jamba 1.5 Mini

Mar 2024

Provider Availability

GPT-4.1 nano is available from OpenAI. Jamba 1.5 Mini is available from Bedrock, Google.

GPT-4.1 nano

openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

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

OpenAI
Larger context window (1,047,576 tokens)
Supports multimodal inputs
Less expensive input tokens
Higher GPQA score (50.3% vs 32.3%)
Higher MMLU score (80.1% vs 69.7%)
AI21 Labs
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4.1 nano
AI21 Labs
Jamba 1.5 Mini

FAQ

Common questions about GPT-4.1 nano vs Jamba 1.5 Mini

GPT-4.1 nano significantly outperforms across most benchmarks. GPT-4.1 nano is made by OpenAI 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.
GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%.
GPT-4.1 nano is 2.0x cheaper for input tokens. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai. Jamba 1.5 Mini costs $0.20/M input and $0.40/M output via bedrock.
GPT-4.1 nano supports 1.0M 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 (1.0M vs 256K), input pricing ($0.10 vs $0.20/M), multimodal support (yes vs no), licensing (Proprietary vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.
GPT-4.1 nano is developed by OpenAI and Jamba 1.5 Mini is developed by AI21 Labs.