Model Comparison

Gemini 1.0 Pro vs Jamba 1.5 MiniWhich is better in 2026?

Both models are evenly matched across the benchmarks. Jamba 1.5 Mini is 3.0x cheaper per token.

Verdict: Gemini 1.0 Pro vs Jamba 1.5 Mini — which is better?

Gemini 1.0 Pro (by Google) 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.

Gemini 1.0 Pro outperforms in 1 benchmarks (MMLU), while Jamba 1.5 Mini is better at 1 benchmark (GPQA). Both models are evenly matched across the benchmarks.

On price, Jamba 1.5 Mini is roughly 3.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Jamba 1.5 Mini also accepts a larger context window (256,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemini 1.0 Pro if…

  • you want predictable pricing at $0.50/M input and $1.50/M output

Choose Jamba 1.5 Mini if…

  • cost matters — it's about 3.0x cheaper per token
  • you process long inputs — it offers a 256,144 token context window
  • you want the most recent training data — it shipped Aug 2024
  • you need open weights you can self-host or fine-tune
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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini 1.0 Pro outperforms in 1 benchmarks (MMLU), while Jamba 1.5 Mini is better at 1 benchmark (GPQA).

Both models are evenly matched across the benchmarks.

Sat Jun 13 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, Gemini 1.0 Pro ($0.50/1M tokens) is 2.5x more expensive than Jamba 1.5 Mini ($0.20/1M tokens).

For output processing, Gemini 1.0 Pro ($1.50/1M tokens) is 3.8x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).

In conclusion, Gemini 1.0 Pro is more expensive than Jamba 1.5 Mini.*

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

Lowest available price from all providers
Sat Jun 13 2026 • llm-stats.com
Google
Gemini 1.0 Pro
Input tokens$0.50
Output tokens$1.50
Best providerGoogle
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

Jamba 1.5 Mini accepts 256,144 input tokens compared to Gemini 1.0 Pro's 32,760 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while Gemini 1.0 Pro is limited to 8,192 tokens.

Google
Gemini 1.0 Pro
Input32,760 tokens
Output8,192 tokens
AI21 Labs
Jamba 1.5 Mini
Input256,144 tokens
Output256,144 tokens
Sat Jun 13 2026 • llm-stats.com

License

Usage and distribution terms

Gemini 1.0 Pro 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.

Gemini 1.0 Pro

Proprietary

Closed source

Jamba 1.5 Mini

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Jamba 1.5 Mini was released on 2024-08-22.

Jamba 1.5 Mini is 6 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.3 years ago

Jamba 1.5 Mini

Aug 22, 2024

1.8 years ago

6mo newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a knowledge cutoff of 2024-02-01, while Jamba 1.5 Mini has a cutoff of 2024-03-05.

Jamba 1.5 Mini has more recent training data (up to 2024-03-05), making it potentially better informed about events through that date compared to Gemini 1.0 Pro (2024-02-01).

Gemini 1.0 Pro

Feb 2024

Jamba 1.5 Mini

Mar 2024

1 mo newer

Provider Availability

Gemini 1.0 Pro is available from Google. Jamba 1.5 Mini is available from Bedrock, Google.

Gemini 1.0 Pro

google logo
Google
Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M

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

Google
Higher MMLU score (71.8% vs 69.7%)
AI21 Labs
Larger context window (256,144 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (32.3% vs 27.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.0 Pro
AI21 Labs
Jamba 1.5 Mini

FAQ

Common questions about Gemini 1.0 Pro vs Jamba 1.5 Mini.

Which is better, Gemini 1.0 Pro or Jamba 1.5 Mini?

Both models are evenly matched across the benchmarks. Gemini 1.0 Pro is made by Google 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 Gemini 1.0 Pro compare to Jamba 1.5 Mini in benchmarks?

Gemini 1.0 Pro scores FLEURS: 93.6%, BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%. Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%.

Is Gemini 1.0 Pro cheaper than Jamba 1.5 Mini?

Jamba 1.5 Mini is 2.5x cheaper for input tokens. Gemini 1.0 Pro costs $0.50/M input and $1.50/M output via google. Jamba 1.5 Mini costs $0.20/M input and $0.40/M output via bedrock.

What are the context window sizes for Gemini 1.0 Pro and Jamba 1.5 Mini?

Gemini 1.0 Pro supports 33K 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 Gemini 1.0 Pro and Jamba 1.5 Mini?

Key differences include context window (33K vs 256K), input pricing ($0.50 vs $0.20/M), licensing (Proprietary vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.0 Pro and Jamba 1.5 Mini?

Gemini 1.0 Pro is developed by Google and Jamba 1.5 Mini is developed by AI21 Labs.

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