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Jamba 1.5 Large vs Parse

Comparing Jamba 1.5 Large and Parse across benchmarks, pricing, and capabilities.

AI21 Labs · Cohere · Updated for 2026

Which is better?

Jamba 1.5 Large and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Jamba 1.5 Large also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Jamba 1.5 Large

  • you process long inputs — it offers a 256,000 token context window
  • you need open weights you can self-host or fine-tune

Choose Parse

  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
Input price
$2.00 / M
— / M
Output price
$8.00 / M
— / M
Context window
256,000
8,192

Individual benchmarks

8 reported for Jamba 1.5 Large · 1 for Parse

No common benchmarks found

Jamba 1.5 Large and Parsedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

395.7B diff

Jamba 1.5 Large has 395.7B more parameters than Parse, making it 17204.3% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
Cohere
Parse
2.3Bparameters
398.0B
Jamba 1.5 Large
2.3B
Parse

Context Window

Maximum input and output token capacity

Jamba 1.5 Large accepts 256,000 input tokens compared to Parse's 8,192 tokens. Only Jamba 1.5 Large specifies output context (256,000 tokens).

AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Mon Aug 31 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Parse supports multimodal inputs, whereas Jamba 1.5 Large does not.

Parse 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

Parse

Text
Images
Audio
Video

License

Usage and distribution terms

Jamba 1.5 Large is licensed under Jamba Open Model License, while Parse uses a proprietary license.

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

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

Jamba 1.5 Large was released on 2024-08-22, while Parse was released on 2026-08-27.

Parse is 25 months newer than Jamba 1.5 Large.

Jamba 1.5 Large

Aug 22, 2024

2.0 years ago

Parse

Aug 27, 2026

3 days ago

2.0yr newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Parse'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 Parse's cutoff date.

Jamba 1.5 Large

Mar 2024

Parse

Provider Availability

Jamba 1.5 Large is available from Bedrock, Google. Parse is available from Azure, Cohere.

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

Parse

azure logo
Azure
cohere logo
Cohere
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Jamba 1.5 Large and Parse side-by-side, then vote on the output you prefer.

Jamba 1.5 Large
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about Jamba 1.5 Large vs Parse.

Which is better, Jamba 1.5 Large or Parse?

Jamba 1.5 Large (AI21 Labs) and Parse (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Jamba 1.5 Large compare to Parse in benchmarks?

Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. Parse scores ParseBench: 79.2%.

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

Jamba 1.5 Large supports 256K tokens and Parse supports 8K 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 Parse?

Key differences include context window (256K vs 8K), multimodal support (no vs yes), licensing (Jamba Open Model License vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Jamba 1.5 Large and Parse?

Jamba 1.5 Large is developed by AI21 Labs and Parse is developed by Cohere.