GPT-5 nano 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-5 nano specs · Jamba 1.5 Large specs- PriceGPT-5 nano
GPT-5 nano is roughly 20.0× cheaper on output tokens ($0.40 vs $8.00 per 1M).
- Context windowGPT-5 nano
GPT-5 nano accepts 400K tokens vs 256K, 1.6× 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-5 nano
GPT-5 nano 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-5 nano is API-only.
On balance GPT-5 nano edges ahead, winning 3 of 5 categories against Jamba 1.5 Large's 1. GPT-5 nano is roughly 20.0× cheaper on output tokens ($0.40 vs $8.00 per 1M). GPT-5 nano accepts 400K tokens vs 256K, 1.6× 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-5 nano 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-5 nano is API-only.
GPT-5 nano is the newer of the two, released 12 months after Jamba 1.5 Large, which usually means a more recent knowledge cutoff and updated safety post-training. GPT-5 nano is usually picked for cheapest llm and fastest llm 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-5 nano | Jamba 1.5 Large |
|---|---|---|
| Provider | OpenAI | AI21 |
| Released | Aug 2025 | Aug 2024 |
| Modalities | text, vision | text |
| Context window | 400K tokens | 256K tokens |
| Max output | 128K tokens | , |
| Input · 1M | $0.050 / 1M tokens | $2.00 / 1M tokens |
| Output · 1M | $0.40 / 1M tokens | $8.00 / 1M tokens |
| Knowledge cutoff | 2024-09 | , |
| 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$0.750 vs $18.00
- Heavy usage, 1M in / 500k out per day$7.50 vs $180
- RAG workload, 5M in / 200k out per day$9.90 vs $348
Light usage, 100k in / 50k out per day: $0.750 vs $18.00 per month, model A comes out ahead. Heavy usage, 1M in / 500k out per day: $7.50 vs $180 per month, model A comes out ahead. RAG workload, 5M in / 200k out per day: $9.90 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-5 nano$0.025
- 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.
GPT-5 nano fits when…
- Lowest-cost OpenAI model with vision support
- Fast P99 latency
- Good enough for routing and classification
- Cost-sensitive workloads, 20.0× cheaper than Jamba 1.5 Large on output tokens.
- Long-context tasks, handles 400K tokens vs 256K for Jamba 1.5 Large.
Jamba 1.5 Large fits when…
- 256k context
- Efficient long-context inference
- Open weights
- 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-5 nano or Jamba 1.5 Large cheaper?
GPT-5 nano is cheaper at $0.40 / 1M tokens per million output tokens, vs $8.00 / 1M tokens for Jamba 1.5 Large.Which has the larger context window?
GPT-5 nano accepts 400K tokens vs 256K for Jamba 1.5 Large.Is GPT-5 nano or Jamba 1.5 Large better for coding?
Both GPT-5 nano 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-5 nano is API-only.When were GPT-5 nano and Jamba 1.5 Large released?
GPT-5 nano was released by OpenAI on 2025-08-07. Jamba 1.5 Large was released by AI21 on 2024-08-22.
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