Model Comparison

Jamba 1.5 Large vs MiniMax M2

MiniMax M2 significantly outperforms across most benchmarks. MiniMax M2 is 6.7x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Jamba 1.5 Large outperforms in 0 benchmarks, while MiniMax M2 is better at 2 benchmarks (GPQA, MMLU-Pro).

MiniMax M2 significantly outperforms across most benchmarks.

Sat May 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

MiniMax M2 costs less

For input processing, Jamba 1.5 Large ($2.00/1M tokens) is 6.7x more expensive than MiniMax M2 ($0.30/1M tokens).

For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 6.7x more expensive than MiniMax M2 ($1.20/1M tokens).

In conclusion, Jamba 1.5 Large is more expensive than MiniMax M2.*

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

Lowest available price from all providers
Sat May 30 2026 • llm-stats.com
AI21 Labs
Jamba 1.5 Large
Input tokens$2.00
Output tokens$8.00
Best providerAWS Bedrock
MiniMax
MiniMax M2
Input tokens$0.30
Output tokens$1.20
Best providerMiniMax
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

168.0B diff

Jamba 1.5 Large has 168.0B more parameters than MiniMax M2, making it 73.0% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
MiniMax
MiniMax M2
230.0Bparameters
398.0B
Jamba 1.5 Large
230.0B
MiniMax M2

Context Window

Maximum input and output token capacity

MiniMax M2 accepts 1,000,000 input tokens compared to Jamba 1.5 Large's 256,000 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while Jamba 1.5 Large is limited to 256,000 tokens.

AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
MiniMax
MiniMax M2
Input1,000,000 tokens
Output1,000,000 tokens
Sat May 30 2026 • llm-stats.com

License

Usage and distribution terms

Jamba 1.5 Large is licensed under Jamba Open Model License, while MiniMax M2 uses MIT.

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

Jamba 1.5 Large

Jamba Open Model License

Open weights

MiniMax M2

MIT

Open weights

Release Timeline

When each model was launched

Jamba 1.5 Large was released on 2024-08-22, while MiniMax M2 was released on 2025-10-27.

MiniMax M2 is 14 months newer than Jamba 1.5 Large.

Jamba 1.5 Large

Aug 22, 2024

1.8 years ago

MiniMax M2

Oct 27, 2025

7 months ago

1.2yr newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while MiniMax M2's cutoff date is not specified.

We can confirm Jamba 1.5 Large's training data extends to 2024-03-05, but cannot make a direct comparison without MiniMax M2's cutoff date.

Jamba 1.5 Large

Mar 2024

MiniMax M2

—

Provider Availability

Jamba 1.5 Large is available from Bedrock, Google. MiniMax M2 is available from MiniMax, Novita.

Jamba 1.5 Large

bedrock logo
AWS Bedrock
Input Price:Input: $2.00/1MOutput Price:Output: $8.00/1M
google logo
Google
Input Price:Input: $2.00/1MOutput Price:Output: $8.00/1M

MiniMax M2

minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

AI21 Labs

No standout differentiators in the data we have for this pair.

MiniMax
Larger context window (1,000,000 tokens)
Less expensive input tokens
Less expensive output tokens
Higher GPQA score (78.0% vs 36.9%)
Higher MMLU-Pro score (82.0% vs 53.5%)

Detailed Comparison

AI Model Comparison Table
Feature
AI21 Labs
Jamba 1.5 Large
MiniMax
MiniMax M2

FAQ

Common questions about Jamba 1.5 Large vs MiniMax M2.

Which is better, Jamba 1.5 Large or MiniMax M2?

MiniMax M2 significantly outperforms across most benchmarks. Jamba 1.5 Large is made by AI21 Labs and MiniMax M2 is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Jamba 1.5 Large compare to MiniMax M2 in benchmarks?

Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. MiniMax M2 scores Tau2 Telecom: 87.0%, LiveCodeBench: 83.0%, MMLU-Pro: 82.0%, AIME 2025: 78.0%, GPQA: 78.0%.

Is Jamba 1.5 Large cheaper than MiniMax M2?

MiniMax M2 is 6.7x cheaper for input tokens. Jamba 1.5 Large costs $2.00/M input and $8.00/M output via bedrock. MiniMax M2 costs $0.30/M input and $1.20/M output via minimax.

What are the context window sizes for Jamba 1.5 Large and MiniMax M2?

Jamba 1.5 Large supports 256K tokens and MiniMax M2 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Jamba 1.5 Large and MiniMax M2?

Key differences include context window (256K vs 1.0M), input pricing ($2.00 vs $0.30/M), licensing (Jamba Open Model License vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Jamba 1.5 Large and MiniMax M2?

Jamba 1.5 Large is developed by AI21 Labs and MiniMax M2 is developed by MiniMax.