Jamba 1.5 Large vs Qwen3.8 Flash
Qwen3.8 Flash leads the LLM Stats Score 49.6 to 1.2. Qwen3.8 Flash is 15.2x cheaper per token.
AI21 Labs · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3.8 Flash leads the overall LLM Stats Score 49.6 to 1.2, ranking #16 overall.
In the 1 individual benchmarks reported for both models, Qwen3.8 Flash wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3.8 Flash is roughly 15.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.8 Flash also accepts a larger context window (1,000,000 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 need open weights you can self-host or fine-tune
Choose Qwen3.8 Flash
- overall performance matters — it scores 49.6 and ranks #16 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 15.2x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for Jamba 1.5 Large · 22 for Qwen3.8 Flash
Jamba 1.5 Large outperforms in 0 benchmarks, while Qwen3.8 Flash is better at 1 benchmark (GPQA).
Qwen3.8 Flash significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Jamba 1.5 Large ($2.00/1M tokens) is 13.3x more expensive than Qwen3.8 Flash ($0.15/1M tokens).
For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 17.0x more expensive than Qwen3.8 Flash ($0.47/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than Qwen3.8 Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Jamba 1.5 Large has 273.0B more parameters than Qwen3.8 Flash, making it 218.4% larger.
Context Window
Maximum input and output token capacity
Qwen3.8 Flash accepts 1,000,000 input tokens compared to Jamba 1.5 Large's 256,000 tokens. Jamba 1.5 Large can generate longer responses up to 256,000 tokens, while Qwen3.8 Flash is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3.8 Flash supports multimodal inputs, whereas Jamba 1.5 Large does not.
Qwen3.8 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
Jamba 1.5 Large
Qwen3.8 Flash
License
Usage and distribution terms
Jamba 1.5 Large is licensed under Jamba Open Model License, while Qwen3.8 Flash uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Jamba Open Model License
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Jamba 1.5 Large was released on 2024-08-22, while Qwen3.8 Flash was released on 2026-08-26.
Qwen3.8 Flash is 24 months newer than Jamba 1.5 Large.
Aug 22, 2024
2.0 years ago
Aug 26, 2026
5 days ago
2.0yr newerKnowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Qwen3.8 Flash'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 Qwen3.8 Flash's cutoff date.
Mar 2024
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Provider Availability
Jamba 1.5 Large is available from Bedrock, Google. Qwen3.8 Flash is available from Novita.
Jamba 1.5 Large
Qwen3.8 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Jamba 1.5 Large and Qwen3.8 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Jamba 1.5 Large vs Qwen3.8 Flash.