GPT-4o mini vs Jamba 1.5 Large
A complete head-to-head: pricing, context window, benchmarks, modality coverage, and openness, with a programmatic verdict synthesized from the underlying data.
Updated
GPT-4o mini specs · Jamba 1.5 Large specs- PriceGPT-4o mini
GPT-4o mini is roughly 13.3× cheaper on output tokens ($0.60 vs $8.00 per 1M).
- Context windowJamba 1.5 Large
Jamba 1.5 Large accepts 256K tokens vs 128K, 2.0× the room for long documents and codebases.
- BenchmarksTie
No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores.
- ModalitiesGPT-4o mini
GPT-4o mini supports 2 modalities (text, vision) vs 1 for Jamba 1.5 Large.
- OpennessJamba 1.5 Large
Jamba 1.5 Large ships open weights (Jamba Open Model License); GPT-4o mini is API-only.
It's a genuine coin-flip between GPT-4o mini and Jamba 1.5 Large: 2 category wins each, with the rest tied. GPT-4o mini is roughly 13.3× cheaper on output tokens ($0.60 vs $8.00 per 1M). Jamba 1.5 Large accepts 256K tokens vs 128K, 2.0× the room for long documents and codebases.
No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores. They differ in modality coverage, GPT-4o mini handles text, vision while Jamba 1.5 Large handles text, which can be the deciding factor before you even look at benchmarks. Jamba 1.5 Large ships open weights (Jamba Open Model License); GPT-4o mini is API-only.
Jamba 1.5 Large is the newer of the two, released 1 months after GPT-4o mini, which usually means a more recent knowledge cutoff and updated safety post-training. GPT-4o mini is usually picked for customer support and summarization workloads, while Jamba 1.5 Large sees more deployments in long context and rag. If pricing matters more than every last benchmark point, run the numbers in the calculator below before committing.
Side-by-side specs
| Spec | GPT-4o mini | Jamba 1.5 Large |
|---|---|---|
| Provider | OpenAI | AI21 |
| Released | Jul 2024 | Aug 2024 |
| Modalities | text, vision | text |
| Context window | 128K tokens | 256K tokens |
| Max output | , | , |
| Input · 1M | $0.15 / 1M tokens | $2.00 / 1M tokens |
| Output · 1M | $0.60 / 1M tokens | $8.00 / 1M tokens |
| Knowledge cutoff | , | , |
| Open weights | No | Yes (Jamba Open Model License) |
| API available | Yes | Yes |
Pricing at scale
What you'd actually pay at typical workloads. Numbers come from each model's published per-million-token rates.
- Light usage, 100k in / 50k out per day$1.35 vs $18.00
- Heavy usage, 1M in / 500k out per day$13.50 vs $180
- RAG workload, 5M in / 200k out per day$26.10 vs $348
Light usage, 100k in / 50k out per day: $1.35 vs $18.00 per month, model A comes out ahead. Heavy usage, 1M in / 500k out per day: $13.50 vs $180 per month, model A comes out ahead. RAG workload, 5M in / 200k out per day: $26.10 vs $348 per month, model A comes out ahead.
Estimated spend for the listed models at your usage. Numbers are derived from each model's published per-million-token rates.
- GPT-4o mini$0.045
- Jamba 1.5 Large$0.600
Benchmarks compared
Only sourced numbers. Where a benchmark is missing for one model we show the available value rather than fabricating the other.
- MMLU82.0
GPT-4o mini fits when…
- Cheap
- Fast
- Mature
- Cost-sensitive workloads, 13.3× cheaper than Jamba 1.5 Large on output tokens.
- Multimodal needs covering vision.
Jamba 1.5 Large fits when…
- 256k context
- Efficient long-context inference
- Open weights
- Long-context tasks, handles 256K tokens vs 128K for GPT-4o mini.
- Self-hosting and on-prem requirements, open weights (Jamba Open Model License).
Consider GPT-5.5
OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.
Frequently asked
Is GPT-4o mini or Jamba 1.5 Large cheaper?
GPT-4o mini is cheaper at $0.60 / 1M tokens per million output tokens, vs $8.00 / 1M tokens for Jamba 1.5 Large.Which has the larger context window?
Jamba 1.5 Large accepts 256K tokens vs 128K for GPT-4o mini.Is GPT-4o mini or Jamba 1.5 Large better for coding?
Both GPT-4o mini and Jamba 1.5 Large are competitive on coding benchmarks. See each model's individual spec page for HumanEval and SWE-bench scores where published. For an opinionated pick, consult our Best LLM for Coding ranking.Are either of these models open source?
Jamba 1.5 Large ships open weights (Jamba Open Model License). GPT-4o mini is API-only.When were GPT-4o mini and Jamba 1.5 Large released?
GPT-4o mini was released by OpenAI on 2024-07-18. Jamba 1.5 Large was released by AI21 on 2024-08-22.
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