Jamba 1.5 Mini vs Qwen3 VL 235B A22B Thinking
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Jamba 1.5 Mini is 4.8x cheaper per token.
AI21 Labs · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Jamba 1.5 Mini outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (MMLU, MMLU-Pro). Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
On price, Jamba 1.5 Mini is roughly 4.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 235B A22B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Jamba 1.5 Mini
- cost matters — it's about 4.8x cheaper per token
Choose Qwen3 VL 235B A22B Thinking
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Jamba 1.5 Mini outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (MMLU, MMLU-Pro).
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Jamba 1.5 Mini ($0.20/1M tokens) is 2.3x cheaper than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, Jamba 1.5 Mini ($0.40/1M tokens) is 8.7x cheaper than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, Qwen3 VL 235B A22B Thinking is more expensive than Jamba 1.5 Mini.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 VL 235B A22B Thinking has 184.0B more parameters than Jamba 1.5 Mini, making it 353.8% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 235B A22B Thinking accepts 262,144 input tokens compared to Jamba 1.5 Mini's 256,144 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while Jamba 1.5 Mini is limited to 256,144 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas Jamba 1.5 Mini does not.
Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Jamba 1.5 Mini
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
Jamba 1.5 Mini is licensed under Jamba Open Model License, while Qwen3 VL 235B A22B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Jamba Open Model License
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Jamba 1.5 Mini was released on 2024-08-22, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.
Qwen3 VL 235B A22B Thinking is 13 months newer than Jamba 1.5 Mini.
Aug 22, 2024
2.0 years ago
Sep 22, 2025
11 months ago
1.1yr newerKnowledge Cutoff
When training data ends
Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while Qwen3 VL 235B A22B Thinking'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 Qwen3 VL 235B A22B Thinking's cutoff date.
Mar 2024
—
Provider Availability
Jamba 1.5 Mini is available from Bedrock, Google. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
Jamba 1.5 Mini
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Jamba 1.5 Mini and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Jamba 1.5 Mini vs Qwen3 VL 235B A22B Thinking.