Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high).
Gemma 4 (Google) and gpt-oss-120b (OpenAI) are two of the models people most often weigh against each other in 2026. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. 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. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: Gemma 4 holds 2× more — 256K (~384 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: Gemma 4 is the newer model by about 8 months (released April 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemma 4
gpt-oss-120b
Provider
Google (US)
OpenAI (US)
Released
April 2, 2026
August 5, 2025
Context window
256K (~384 pages)
131K (~197 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
62.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Self-hosted, data-private deployment: Gemma 4 — A core design strength of Gemma 4.
Running locally or on edge devices: Gemma 4 — A core design strength of Gemma 4.
Fine-tuning on your own data: Gemma 4 — A core design strength of Gemma 4.
Self-hostable on a single 80GB H100 GPU via MXFP4: gpt-oss-120b — A core design strength of gpt-oss-120b.
Configurable reasoning depth (low/medium/high): gpt-oss-120b — A core design strength of gpt-oss-120b.
Agentic tool use, function calling, and code execution: gpt-oss-120b — A core design strength of gpt-oss-120b.
Largest single-prompt input: Gemma 4 — Its 256K window is about 2× larger, fitting roughly 384 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases: Gemma 4 — Larger 256K window fits more in one prompt.
Anyone whose priority is self-hosted, data-private deployment: Gemma 4 — It is specifically built for that.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4: gpt-oss-120b — That is its strongest area.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs are real: trails frontier closed models on the hardest tasks, and needs your own hardware to run. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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: 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.
The bottom line for this matchup
Gemma 4 and gpt-oss-120b overlap enough that the right pick depends on your specific job. Gemma 4 holds the larger context; and each leads in its own area — Gemma 4 for self-hosted, data-private deployment, gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Gemma 4 or gpt-oss-120b better for coding?
Public SWE-Bench figures are not available for Gemma 4, so the honest test is your own repository — run an identical real bug through both. By design, Gemma 4 leans toward self-hosted, data-private deployment while gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 or gpt-oss-120b?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Gemma 4 — 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 Gemma 4 and gpt-oss-120b together?
Yes — a multi-model platform like LumiChats gives you Gemma 4, gpt-oss-120b 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, Gemma 4 or gpt-oss-120b?
Gemma 4 — released April 2, 2026, about 8 months after gpt-oss-120b.
Gemma 4 vs gpt-oss-120b
Google · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high).
Gemma 4 (Google) and gpt-oss-120b (OpenAI) are two of the models people most often weigh against each other in 2026. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. 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. 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: Gemma 4 holds 2× more — 256K (~384 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: Gemma 4 is the newer model by about 8 months (released April 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemma 4
gpt-oss-120b
Provider
Google (US)
OpenAI (US)
Released
April 2, 2026
August 5, 2025
Context window
256K (~384 pages)
131K (~197 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
62.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Self-hosted, data-private deployment
Gemma 4
A core design strength of Gemma 4.
Running locally or on edge devices
Gemma 4
A core design strength of Gemma 4.
Fine-tuning on your own data
Gemma 4
A core design strength of Gemma 4.
Self-hostable on a single 80GB H100 GPU via MXFP4
gpt-oss-120b
A core design strength of gpt-oss-120b.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
A core design strength of gpt-oss-120b.
Agentic tool use, function calling, and code execution
gpt-oss-120b
A core design strength of gpt-oss-120b.
Largest single-prompt input
Gemma 4
Its 256K window is about 2× larger, fitting roughly 384 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Gemma 4
Larger 256K window fits more in one prompt.
Anyone whose priority is self-hosted, data-private deployment
→ Gemma 4
It is specifically built for that.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4
→ gpt-oss-120b
That is its strongest area.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs are real: trails frontier closed models on the hardest tasks, and needs your own hardware to run. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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: 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.
The bottom line for this matchup
Gemma 4 and gpt-oss-120b overlap enough that the right pick depends on your specific job. Gemma 4 holds the larger context; and each leads in its own area — Gemma 4 for self-hosted, data-private deployment, gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Gemma 4 and gpt-oss-120b 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.
Public SWE-Bench figures are not available for Gemma 4, so the honest test is your own repository — run an identical real bug through both. By design, Gemma 4 leans toward self-hosted, data-private deployment while gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 or gpt-oss-120b?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Gemma 4 — 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 Gemma 4 and gpt-oss-120b together?
Yes — a multi-model platform like LumiChats gives you Gemma 4, gpt-oss-120b 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, Gemma 4 or gpt-oss-120b?
Gemma 4 — released April 2, 2026, about 8 months after gpt-oss-120b.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.