Model Comparison

GLM-4.5V vs Jamba 1.5 Large

Comparing GLM-4.5V and Jamba 1.5 Large across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-4.5V and Jamba 1.5 Large don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GLM-4.5V costs less

For input processing, GLM-4.5V ($0.55/1M tokens) is 3.6x cheaper than Jamba 1.5 Large ($2.00/1M tokens).

For output processing, GLM-4.5V ($2.19/1M tokens) is 3.7x cheaper than Jamba 1.5 Large ($8.00/1M tokens).

In conclusion, Jamba 1.5 Large is more expensive than GLM-4.5V.*

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

Lowest available price from all providers
Wed Apr 22 2026 • llm-stats.com
Zhipu AI
GLM-4.5V
Input tokens$0.55
Output tokens$2.19
Best providerFireworks
AI21 Labs
Jamba 1.5 Large
Input tokens$2.00
Output tokens$8.00
Best providerAWS Bedrock
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

290.0B diff

Jamba 1.5 Large has 290.0B more parameters than GLM-4.5V, making it 268.5% larger.

Zhipu AI
GLM-4.5V
108.0Bparameters
AI21 Labs
Jamba 1.5 Large
398.0Bparameters
108.0B
GLM-4.5V
398.0B
Jamba 1.5 Large

Context Window

Maximum input and output token capacity

Jamba 1.5 Large accepts 256,000 input tokens compared to GLM-4.5V's 131,072 tokens. Jamba 1.5 Large can generate longer responses up to 256,000 tokens, while GLM-4.5V is limited to 131,072 tokens.

Zhipu AI
GLM-4.5V
Input131,072 tokens
Output131,072 tokens
AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
Wed Apr 22 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-4.5V supports multimodal inputs, whereas Jamba 1.5 Large does not.

GLM-4.5V can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.5V

Text
Images
Audio
Video

Jamba 1.5 Large

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.5V is licensed under MIT, while Jamba 1.5 Large uses Jamba Open Model License.

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

GLM-4.5V

MIT

Open weights

Jamba 1.5 Large

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

GLM-4.5V was released on 2025-08-11, while Jamba 1.5 Large was released on 2024-08-22.

GLM-4.5V is 12 months newer than Jamba 1.5 Large.

GLM-4.5V

Aug 11, 2025

8 months ago

11mo newer
Jamba 1.5 Large

Aug 22, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while GLM-4.5V'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 GLM-4.5V's cutoff date.

GLM-4.5V

—

Jamba 1.5 Large

Mar 2024

Provider Availability

GLM-4.5V is available from Fireworks, Novita. Jamba 1.5 Large is available from Bedrock, Google.

GLM-4.5V

fireworks logo
Fireworks
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M

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
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Zhipu AI
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
AI21 Labs
Larger context window (256,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-4.5V
AI21 Labs
Jamba 1.5 Large

FAQ

Common questions about GLM-4.5V vs Jamba 1.5 Large

GLM-4.5V (Zhipu AI) and Jamba 1.5 Large (AI21 Labs) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%.
GLM-4.5V is 3.6x cheaper for input tokens. GLM-4.5V costs $0.55/M input and $2.19/M output via fireworks. Jamba 1.5 Large costs $2.00/M input and $8.00/M output via bedrock.
GLM-4.5V supports 131K tokens and Jamba 1.5 Large supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 256K), input pricing ($0.55 vs $2.00/M), multimodal support (yes vs no), licensing (MIT vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.
GLM-4.5V is developed by Zhipu AI and Jamba 1.5 Large is developed by AI21 Labs.