gpt-oss-120b vs Jamba2 Mini
OpenAI · US | AI21 Labs · Israel · Updated June 2026
Quick verdict
Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Pick Jamba2 Mini for a genuinely different architecture - hybrid mamba (ssm) + transformer, not another transformer variant or fast, efficient long-context inference tuned for enterprise workloads.
gpt-oss-120b (OpenAI, US) and Jamba2 Mini (AI21 Labs, Israel) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. gpt-oss-120b is openAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Jamba2 Mini is aI21's hybrid Mamba-Transformer model - a genuinely different architecture built for fast, efficient long-context enterprise work, free to self-host under Apache 2.0. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Context window: Jamba2 Mini holds 2× more — 256K (~393 pages) vs 131K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Jamba2 Mini is the newer model by about 5 months (released January 8, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a US-vs-Israel matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | gpt-oss-120b | Jamba2 Mini |
|---|---|---|
| Provider | OpenAI (US) | AI21 Labs (Israel) |
| Released | August 5, 2025 | January 8, 2026 |
| Context window | 131K (~197 pages) | 256K (~393 pages) |
| Price (in/out) | Open weight (self-host / free) | Open weight (self-host / free) |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, code | text, code |
| SWE-Bench Verified | 62.4% | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Self-hostable on a single 80GB H100 GPU via MXFP4
gpt-oss-120b
gpt-oss-120b lists self-hostable on a single 80GB H100 GPU via MXFP4 among its strengths; Jamba2 Mini does not.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
Jamba2 Mini is comparatively weak here — tuned for grounded, steerable enterprise tasks rather than topping general reasoning leaderboards
Agentic tool use, function calling, and code execution
gpt-oss-120b
gpt-oss-120b lists agentic tool use, function calling, and code execution among its strengths; Jamba2 Mini does not.
A genuinely different architecture - hybrid Mamba (SSM) + Transformer, not another transformer variant
Jamba2 Mini
AI21's hybrid Mamba-Transformer model - a genuinely different architecture built for fast, efficient long-context enterprise work, free to self-host under Apache 2.0 — and it carries the larger 256K context.
Fast, efficient long-context inference tuned for enterprise workloads
Jamba2 Mini
Its 256K window holds about 2× more than gpt-oss-120b's 131K in a single prompt.
Open weights (Apache 2.0) - free to self-host
Jamba2 Mini
AI21's hybrid Mamba-Transformer model - a genuinely different architecture built for fast, efficient long-context enterprise work, free to self-host under Apache 2.0 — and it is the newer of the two.
Largest single-prompt input
Jamba2 Mini
Its 256K window is about 2× larger than gpt-oss-120b's 131K, fitting roughly 393 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Jamba2 Mini
Larger 256K window fits more in one prompt.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4
→ gpt-oss-120b
It is specifically built for that.
Anyone whose priority is a genuinely different architecture - hybrid mamba (ssm) + transformer, not another transformer variant
→ Jamba2 Mini
That is its strongest area.
An enterprise with regional data-residency rules
→ gpt-oss-120b or Jamba2 Mini
Origin (US vs Israel) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
gpt-oss-120b: where it fits
OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Released August 5, 2025 by OpenAI, it is built for self-hostable on a single 80GB H100 GPU via MXFP4, configurable reasoning depth (low/medium/high), agentic tool use, function calling, and code execution, and full chain-of-thought visibility for debugging.
Its trade-offs are real: text-only, no image, audio, or video input, and 131K context and 5.1B active params trail the largest frontier closed models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
Jamba2 Mini: where it fits
AI21's hybrid Mamba-Transformer model - a genuinely different architecture built for fast, efficient long-context enterprise work, free to self-host under Apache 2.0. Released January 8, 2026 by AI21 Labs, it is built for a genuinely different architecture - hybrid Mamba (SSM) + Transformer, not another transformer variant, fast, efficient long-context inference tuned for enterprise workloads, open weights (Apache 2.0) - free to self-host, and a 52B-total/12B-active MoE design that's cheap to run relative to its capability.
Its trade-offs: tuned for grounded, steerable enterprise tasks rather than topping general reasoning leaderboards, no official per-token API price published - self-host or use AI21's platform preview, and newer architecture family means less third-party tooling support than mainstream transformers. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." gpt-oss-120b (US) and Jamba2 Mini (Israel) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both gpt-oss-120b and Jamba2 Mini without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is gpt-oss-120b or Jamba2 Mini better for coding?
Public SWE-Bench figures are not available for Jamba2 Mini, so the honest test is your own repository — run an identical real bug through both. By design, gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4 while Jamba2 Mini leans toward a genuinely different architecture - hybrid mamba (ssm) + transformer, not another transformer variant, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, gpt-oss-120b or Jamba2 Mini?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Jamba2 Mini — 256K vs 131K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both gpt-oss-120b and Jamba2 Mini together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, Jamba2 Mini and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, gpt-oss-120b or Jamba2 Mini?
Jamba2 Mini — released January 8, 2026, about 5 months after gpt-oss-120b.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.