Model Comparison

GPT-5.6 Luna vs Jamba 1.5 MiniWhich is better in 2026?

GPT-5.6 Luna significantly outperforms across most benchmarks. Jamba 1.5 Mini is 9.0x cheaper per token.

Verdict: GPT-5.6 Luna vs Jamba 1.5 Mini — which is better?

GPT-5.6 Luna (by OpenAI) and Jamba 1.5 Mini (by AI21 Labs) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

GPT-5.6 Luna outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Mini is better at 0 benchmarks. GPT-5.6 Luna significantly outperforms across most benchmarks.

On price, Jamba 1.5 Mini is roughly 9.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GPT-5.6 Luna also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose GPT-5.6 Luna if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you process long inputs — it offers a 1,050,000 token context window
  • you want the most recent training data — it shipped Jul 2026

Choose Jamba 1.5 Mini if…

  • cost matters — it's about 9.0x cheaper per token
  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GPT-5.6 Luna outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Mini is better at 0 benchmarks.

GPT-5.6 Luna significantly outperforms across most benchmarks.

Sun Jul 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Jamba 1.5 Mini costs less

For input processing, GPT-5.6 Luna ($1.00/1M tokens) is 5.0x more expensive than Jamba 1.5 Mini ($0.20/1M tokens).

For output processing, GPT-5.6 Luna ($6.00/1M tokens) is 15.0x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).

In conclusion, GPT-5.6 Luna is more expensive than Jamba 1.5 Mini.*

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

Lowest available price from all providers
Sun Jul 19 2026 • llm-stats.com
OpenAI
GPT-5.6 Luna
Input tokens$1.00
Output tokens$6.00
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-5.6 Luna accepts 1,050,000 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-5.6 Luna is limited to 128,000 tokens.

OpenAI
GPT-5.6 Luna
Input1,050,000 tokens
Output128,000 tokens
AI21 Labs
Jamba 1.5 Mini
Input256,144 tokens
Output256,144 tokens
Sun Jul 19 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.6 Luna supports multimodal inputs, whereas Jamba 1.5 Mini does not.

GPT-5.6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-5.6 Luna

Text
Images
Audio
Video

Jamba 1.5 Mini

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-5.6 Luna 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-5.6 Luna

Proprietary

Closed source

Jamba 1.5 Mini

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

GPT-5.6 Luna was released on 2026-07-09, while Jamba 1.5 Mini was released on 2024-08-22.

GPT-5.6 Luna is 23 months newer than Jamba 1.5 Mini.

GPT-5.6 Luna

Jul 9, 2026

1 weeks ago

1.9yr newer
Jamba 1.5 Mini

Aug 22, 2024

1.9 years ago

Knowledge Cutoff

When training data ends

GPT-5.6 Luna has a knowledge cutoff of 2026-02-16, while Jamba 1.5 Mini has a cutoff of 2024-03-05.

GPT-5.6 Luna has more recent training data (up to 2026-02-16), making it potentially better informed about events through that date compared to Jamba 1.5 Mini (2024-03-05).

GPT-5.6 Luna

Feb 2026

1.9 yr newer
Jamba 1.5 Mini

Mar 2024

Provider Availability

GPT-5.6 Luna is available from OpenAI. Jamba 1.5 Mini is available from Bedrock, Google.

GPT-5.6 Luna

openai logo
OpenAI
Input Price:Input: $1.00/1MOutput Price:Output: $6.00/1M

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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

OpenAI
Larger context window (1,050,000 tokens)
Supports multimodal inputs
Higher GPQA score (92.3% vs 32.3%)
AI21 Labs
Less expensive input tokens
Less expensive output tokens
Has open weights

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GPT-5.6 Luna and Jamba 1.5 Mini side-by-side, then vote on the output you prefer.

GPT-5.6 Luna
✓ Preferred
Jamba 1.5 Mini
Open in Playground
AI Model Comparison Table
Feature
OpenAI
GPT-5.6 Luna
AI21 Labs
Jamba 1.5 Mini

FAQ

Common questions about GPT-5.6 Luna vs Jamba 1.5 Mini.

Which is better, GPT-5.6 Luna or Jamba 1.5 Mini?

GPT-5.6 Luna significantly outperforms across most benchmarks. GPT-5.6 Luna 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.

How does GPT-5.6 Luna compare to Jamba 1.5 Mini in benchmarks?

GPT-5.6 Luna scores Connectors: 99.9%, HealthBench Consensus: 95.1%, GPQA: 92.3%, Search and Function-Calling: 89.7%, Capture-the-Flag Challenges (Internal): 85.2%. Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%.

Is GPT-5.6 Luna cheaper than Jamba 1.5 Mini?

Jamba 1.5 Mini is 5.0x cheaper for input tokens. GPT-5.6 Luna costs $1.00/M input and $6.00/M output via openai. Jamba 1.5 Mini costs $0.20/M input and $0.40/M output via bedrock.

What are the context window sizes for GPT-5.6 Luna and Jamba 1.5 Mini?

GPT-5.6 Luna supports 1.1M 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.

What are the main differences between GPT-5.6 Luna and Jamba 1.5 Mini?

Key differences include context window (1.1M vs 256K), input pricing ($1.00 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.

Who makes GPT-5.6 Luna and Jamba 1.5 Mini?

GPT-5.6 Luna is developed by OpenAI and Jamba 1.5 Mini is developed by AI21 Labs.

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