DeepSeek-V4-Flash-Vision-Exp vs Jamba 1.5 Large
Comparing DeepSeek-V4-Flash-Vision-Exp and Jamba 1.5 Large across benchmarks, pricing, and capabilities.
DeepSeek · AI21 Labs · Updated for 2026
Which is better?
DeepSeek-V4-Flash-Vision-Exp and Jamba 1.5 Large trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V4-Flash-Vision-Exp is roughly 10.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-Vision-Exp 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 DeepSeek-V4-Flash-Vision-Exp
- cost matters — it's about 10.6x 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 Large
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-Vision-Exp and Jamba 1.5 Largedon'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, DeepSeek-V4-Flash-Vision-Exp ($0.22/1M tokens) is 9.1x cheaper than Jamba 1.5 Large ($2.00/1M tokens).
For output processing, DeepSeek-V4-Flash-Vision-Exp ($0.66/1M tokens) is 12.1x cheaper than Jamba 1.5 Large ($8.00/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than DeepSeek-V4-Flash-Vision-Exp.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-Vision-Exp accepts 1,048,576 input tokens compared to Jamba 1.5 Large's 256,000 tokens. DeepSeek-V4-Flash-Vision-Exp can generate longer responses up to 393,216 tokens, while Jamba 1.5 Large is limited to 256,000 tokens.
Input Capabilities
Supported data types and modalities
DeepSeek-V4-Flash-Vision-Exp supports multimodal inputs, whereas Jamba 1.5 Large does not.
DeepSeek-V4-Flash-Vision-Exp can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-Vision-Exp
Jamba 1.5 Large
Release Timeline
When each model was launched
DeepSeek-V4-Flash-Vision-Exp was released on 2026-08-21, while Jamba 1.5 Large was released on 2024-08-22.
DeepSeek-V4-Flash-Vision-Exp is 24 months newer than Jamba 1.5 Large.
Aug 21, 2026
3 days ago
2.0yr newerAug 22, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while DeepSeek-V4-Flash-Vision-Exp'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 DeepSeek-V4-Flash-Vision-Exp's cutoff date.
—
Mar 2024
Provider Availability
DeepSeek-V4-Flash-Vision-Exp is available from DeepSeek. Jamba 1.5 Large is available from Bedrock, Google.
DeepSeek-V4-Flash-Vision-Exp
Jamba 1.5 Large
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Vision-Exp and Jamba 1.5 Large side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-Vision-Exp vs Jamba 1.5 Large.