GLM-5.3-Flash vs Jamba 1.5 Mini
Comparing GLM-5.3-Flash and Jamba 1.5 Mini across benchmarks, pricing, and capabilities.
Zhipu AI · AI21 Labs · Updated for 2026
Which is better?
GLM-5.3-Flash and Jamba 1.5 Mini trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, GLM-5.3-Flash is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3-Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose GLM-5.3-Flash
- cost matters — it's about 1.1x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Jamba 1.5 Mini
- you want predictable pricing at $0.20/M input and $0.40/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3-Flash and Jamba 1.5 Minidon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3-Flash ($0.15/1M tokens) is 1.3x cheaper than Jamba 1.5 Mini ($0.20/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 1.3x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).
In conclusion, Jamba 1.5 Mini is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 268.0B more parameters than Jamba 1.5 Mini, making it 515.4% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Jamba 1.5 Mini's 256,144 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while GLM-5.3-Flash is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
GLM-5.3-Flash supports multimodal inputs, whereas Jamba 1.5 Mini does not.
GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3-Flash
Jamba 1.5 Mini
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, 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.
MIT
Open weights
Jamba Open Model License
Open weights
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Jamba 1.5 Mini was released on 2024-08-22.
GLM-5.3-Flash is 24 months newer than Jamba 1.5 Mini.
Aug 26, 2026
0 days ago
2.0yr newerAug 22, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while GLM-5.3-Flash's cutoff date is not specified.
We can confirm Jamba 1.5 Mini's training data extends to 2024-03-05, but cannot make a direct comparison without GLM-5.3-Flash's cutoff date.
—
Mar 2024
Provider Availability
GLM-5.3-Flash is available from DeepInfra, Novita, ZAI. Jamba 1.5 Mini is available from Bedrock, Google.
GLM-5.3-Flash
Jamba 1.5 Mini
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Jamba 1.5 Mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Jamba 1.5 Mini.