DeepSeek-V4.1-Flash vs Jamba 1.5 Large
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 0.9. DeepSeek-V4.1-Flash is 10.6x cheaper per token.
DeepSeek · AI21 Labs · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 0.9, ranking #12 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash is roughly 10.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 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 DeepSeek-V4.1-Flash
- overall performance matters — it scores 51.8 and ranks #12 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 10.6x cheaper per token
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Jamba 1.5 Large
- you want predictable pricing at $2.00/M input and $8.00/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 8 for Jamba 1.5 Large
DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Large is better at 0 benchmarks.
DeepSeek-V4.1-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, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 9.1x cheaper than Jamba 1.5 Large ($2.00/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($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-V4.1-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash has 365.2B more parameters than Jamba 1.5 Large, making it 91.8% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Jamba 1.5 Large's 256,000 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Jamba 1.5 Large is limited to 256,000 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas Jamba 1.5 Large does not.
DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4.1-Flash
Jamba 1.5 Large
License
Usage and distribution terms
DeepSeek-V4.1-Flash 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.
MIT
Open weights
Jamba Open Model License
Open weights
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash was released on 2026-09-10, while Jamba 1.5 Large was released on 2024-08-22.
DeepSeek-V4.1-Flash is 25 months newer than Jamba 1.5 Large.
Sep 10, 2026
0 days ago
2.1yr newerAug 22, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while DeepSeek-V4.1-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 DeepSeek-V4.1-Flash's cutoff date.
—
Mar 2024
Provider Availability
DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. Jamba 1.5 Large is available from Bedrock, Google.
DeepSeek-V4.1-Flash
Jamba 1.5 Large
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Jamba 1.5 Large side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Jamba 1.5 Large.