Model Comparison

Jamba 1.5 Large vs Mistral Large 3 (675B Instruct 2512)Which is better in 2026?

Mistral Large 3 (675B Instruct 2512) significantly outperforms across most benchmarks. Mistral Large 3 (675B Instruct 2512) is 4.7x cheaper per token.

Verdict: Jamba 1.5 Large vs Mistral Large 3 (675B Instruct 2512) — which is better?

Jamba 1.5 Large (by AI21 Labs) and Mistral Large 3 (675B Instruct 2512) (by Mistral AI) 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.

Jamba 1.5 Large outperforms in 0 benchmarks, while Mistral Large 3 (675B Instruct 2512) is better at 1 benchmark (GPQA). Mistral Large 3 (675B Instruct 2512) significantly outperforms across most benchmarks.

On price, Mistral Large 3 (675B Instruct 2512) is roughly 4.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Mistral Large 3 (675B Instruct 2512) also accepts a larger context window (262,100 input tokens), making it the stronger choice for long documents and large codebases.

Choose Jamba 1.5 Large if…

  • you want predictable pricing at $2.00/M input and $8.00/M output

Choose Mistral Large 3 (675B Instruct 2512) if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • cost matters — it's about 4.7x cheaper per token
  • you process long inputs — it offers a 262,100 token context window
  • you want the most recent training data — it shipped Dec 2025

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Jamba 1.5 Large outperforms in 0 benchmarks, while Mistral Large 3 (675B Instruct 2512) is better at 1 benchmark (GPQA).

Mistral Large 3 (675B Instruct 2512) significantly outperforms across most benchmarks.

Sat Jun 27 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Mistral Large 3 (675B Instruct 2512) costs less

For input processing, Jamba 1.5 Large ($2.00/1M tokens) is 4.0x more expensive than Mistral Large 3 (675B Instruct 2512) ($0.50/1M tokens).

For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 5.3x more expensive than Mistral Large 3 (675B Instruct 2512) ($1.50/1M tokens).

In conclusion, Jamba 1.5 Large is more expensive than Mistral Large 3 (675B Instruct 2512).*

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

Lowest available price from all providers
Sat Jun 27 2026 • llm-stats.com
AI21 Labs
Jamba 1.5 Large
Input tokens$2.00
Output tokens$8.00
Best providerAWS Bedrock
Mistral AI
Mistral Large 3 (675B Instruct 2512)
Input tokens$0.50
Output tokens$1.50
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

277.0B diff

Mistral Large 3 (675B Instruct 2512) has 277.0B more parameters than Jamba 1.5 Large, making it 69.6% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
Mistral AI
Mistral Large 3 (675B Instruct 2512)
675.0Bparameters
398.0B
Jamba 1.5 Large
675.0B
Mistral Large 3 (675B Instruct 2512)

Context Window

Maximum input and output token capacity

Mistral Large 3 (675B Instruct 2512) accepts 262,100 input tokens compared to Jamba 1.5 Large's 256,000 tokens. Mistral Large 3 (675B Instruct 2512) can generate longer responses up to 262,100 tokens, while Jamba 1.5 Large is limited to 256,000 tokens.

AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
Mistral AI
Mistral Large 3 (675B Instruct 2512)
Input262,100 tokens
Output262,100 tokens
Sat Jun 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Large 3 (675B Instruct 2512) supports multimodal inputs, whereas Jamba 1.5 Large does not.

Mistral Large 3 (675B Instruct 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.

Jamba 1.5 Large

Text
Images
Audio
Video

Mistral Large 3 (675B Instruct 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

Jamba 1.5 Large is licensed under Jamba Open Model License, while Mistral Large 3 (675B Instruct 2512) uses Apache 2.0.

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

Mistral Large 3 (675B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

Jamba 1.5 Large was released on 2024-08-22, while Mistral Large 3 (675B Instruct 2512) was released on 2025-12-04.

Mistral Large 3 (675B Instruct 2512) is 16 months newer than Jamba 1.5 Large.

Jamba 1.5 Large

Aug 22, 2024

1.8 years ago

Mistral Large 3 (675B Instruct 2512)

Dec 4, 2025

6 months ago

1.3yr newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Mistral Large 3 (675B Instruct 2512)'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 Mistral Large 3 (675B Instruct 2512)'s cutoff date.

Jamba 1.5 Large

Mar 2024

Mistral Large 3 (675B Instruct 2512)

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Provider Availability

Jamba 1.5 Large is available from Bedrock, Google. Mistral Large 3 (675B Instruct 2512) is available from Mistral AI.

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

Mistral Large 3 (675B Instruct 2512)

mistral logo
Mistral
Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

AI21 Labs

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

Mistral AI
Larger context window (262,100 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Higher GPQA score (43.9% vs 36.9%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Jamba 1.5 Large and Mistral Large 3 (675B Instruct 2512) side-by-side, then vote on the output you prefer.

Jamba 1.5 Large
✓ Preferred
Mistral Large 3 (675B Instruct 2512)
Open in Playground
AI Model Comparison Table
Feature
AI21 Labs
Jamba 1.5 Large
Mistral AI
Mistral Large 3 (675B Instruct 2512)

FAQ

Common questions about Jamba 1.5 Large vs Mistral Large 3 (675B Instruct 2512).

Which is better, Jamba 1.5 Large or Mistral Large 3 (675B Instruct 2512)?

Mistral Large 3 (675B Instruct 2512) significantly outperforms across most benchmarks. Jamba 1.5 Large is made by AI21 Labs and Mistral Large 3 (675B Instruct 2512) is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Jamba 1.5 Large compare to Mistral Large 3 (675B Instruct 2512) in benchmarks?

Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. Mistral Large 3 (675B Instruct 2512) scores MMMLU: 85.5%, AMC_2022_23: 52.0%, GPQA: 43.9%, LiveCodeBench: 34.4%, SimpleQA: 23.8%.

Is Jamba 1.5 Large cheaper than Mistral Large 3 (675B Instruct 2512)?

Mistral Large 3 (675B Instruct 2512) is 4.0x cheaper for input tokens. Jamba 1.5 Large costs $2.00/M input and $8.00/M output via bedrock. Mistral Large 3 (675B Instruct 2512) costs $0.50/M input and $1.50/M output via mistral.

What are the context window sizes for Jamba 1.5 Large and Mistral Large 3 (675B Instruct 2512)?

Jamba 1.5 Large supports 256K tokens and Mistral Large 3 (675B Instruct 2512) supports 262K 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 Mistral Large 3 (675B Instruct 2512)?

Key differences include context window (256K vs 262K), input pricing ($2.00 vs $0.50/M), multimodal support (no vs yes), licensing (Jamba Open Model License vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Jamba 1.5 Large and Mistral Large 3 (675B Instruct 2512)?

Jamba 1.5 Large is developed by AI21 Labs and Mistral Large 3 (675B Instruct 2512) is developed by Mistral AI.

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