GPT-4 vs Jamba 1.5 Mini
GPT-4 leads the LLM Stats Score 3.3 to -5.5. Jamba 1.5 Mini is 150.0x cheaper per token.
OpenAI · AI21 Labs · Updated for 2026
Which is better?
GPT-4 leads the overall LLM Stats Score 3.3 to -5.5, ranking #293 overall.
In the 2 individual benchmarks reported for both models, GPT-4 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Jamba 1.5 Mini is roughly 150.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Jamba 1.5 Mini also accepts a larger context window (256,144 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 GPT-4
- overall performance matters — it scores 3.3 and ranks #293 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
Choose Jamba 1.5 Mini
- cost matters — it's about 150.0x cheaper per token
- you process long inputs — it offers a 256,144 token context window
- you want the most recent training data — it shipped Aug 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for GPT-4 · 8 for Jamba 1.5 Mini
GPT-4 outperforms in 2 benchmarks (GPQA, MMLU), while Jamba 1.5 Mini is better at 0 benchmarks.
GPT-4 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, GPT-4 ($30.00/1M tokens) is 150.0x more expensive than Jamba 1.5 Mini ($0.20/1M tokens).
For output processing, GPT-4 ($60.00/1M tokens) is 150.0x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).
In conclusion, GPT-4 is more expensive than Jamba 1.5 Mini.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Jamba 1.5 Mini accepts 256,144 input tokens compared to GPT-4's 32,768 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while GPT-4 is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4 supports multimodal inputs, whereas Jamba 1.5 Mini does not.
GPT-4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4
Jamba 1.5 Mini
License
Usage and distribution terms
GPT-4 is licensed under a proprietary license, 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.
Proprietary
Closed source
Jamba Open Model License
Open weights
Release Timeline
When each model was launched
GPT-4 was released on 2023-06-13, while Jamba 1.5 Mini was released on 2024-08-22.
Jamba 1.5 Mini is 15 months newer than GPT-4.
Jun 13, 2023
3.2 years ago
Aug 22, 2024
2.0 years ago
1.2yr newerKnowledge Cutoff
When training data ends
GPT-4 has a knowledge cutoff of 2022-12-31, while Jamba 1.5 Mini has a cutoff of 2024-03-05.
Jamba 1.5 Mini has more recent training data (up to 2024-03-05), making it potentially better informed about events through that date compared to GPT-4 (2022-12-31).
Dec 2022
Mar 2024
1.3 yr newerProvider Availability
GPT-4 is available from Azure, OpenAI. Jamba 1.5 Mini is available from Bedrock, Google.
GPT-4
Jamba 1.5 Mini
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4 and Jamba 1.5 Mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4 vs Jamba 1.5 Mini.