Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Pick MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai or ranked in the top 15 on lm arena at launch. Choose gpt-oss-120b if you need self-hosting or data privacy; MAI-1-preview if you want a managed API.
gpt-oss-120b (OpenAI) and MAI-1-preview (Microsoft) are two of the models people most often weigh against each other in 2026. 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. MAI-1-preview is microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. They diverge most on context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: gpt-oss-120b ships open weights you can self-host (hardware cost only, no per-token fee), while MAI-1-preview is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: 131K vs 128K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: MAI-1-preview is the newer model by about 23 days (released August 28, 2025), usually meaning fresher training data and capabilities.
Specifications
Spec
gpt-oss-120b
MAI-1-preview
Provider
OpenAI (US)
Microsoft (US)
Released
August 5, 2025
August 28, 2025
Context window
131K (~197 pages)
128K (~192 pages)
Price (in/out)
Open weight (self-host / free)
Not published
Open weight?
Yes — self-hostable
No — API only
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 — Open weights make this possible at all — MAI-1-preview is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high): gpt-oss-120b — MAI-1-preview is comparatively weak here — distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry
Agentic tool use, function calling, and code execution: gpt-oss-120b — 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 — and its weights are open while MAI-1-preview is API-only.
Microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI: MAI-1-preview — gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models
Ranked in the top 15 on LM Arena at launch: MAI-1-preview — Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs — and it is the newer of the two.
Trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment: MAI-1-preview — MAI-1-preview lists trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment among its strengths; gpt-oss-120b does not.
Which should you pick?
Someone analysing very long documents or codebases: gpt-oss-120b — Larger 131K window fits more in one prompt.
A team with data-privacy or self-hosting needs: gpt-oss-120b — Open weights let you run it on your own hardware; MAI-1-preview is API-only.
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 microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai: MAI-1-preview — That is its strongest area.
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.
MAI-1-preview: where it fits
Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Released August 28, 2025 by Microsoft, it is built for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI, ranked in the top 15 on LM Arena at launch, trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment, and rolled into Copilot alongside OpenAI models, giving Microsoft a real second option.
Its trade-offs: a 'preview' release, not yet positioned as Microsoft's primary Copilot model, no public per-token API pricing - not sold as a standalone product, and distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry.
The bottom line for this matchup
The defining split here is open vs. closed. gpt-oss-120b gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. MAI-1-preview gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is gpt-oss-120b or MAI-1-preview better for coding?
Public SWE-Bench figures are not available for MAI-1-preview, 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 MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, gpt-oss-120b or MAI-1-preview?
gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while MAI-1-preview is API-metered at Not published. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Effectively neither — 131K vs 128K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both gpt-oss-120b and MAI-1-preview together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, MAI-1-preview 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 MAI-1-preview?
MAI-1-preview — released August 28, 2025, about 23 days after gpt-oss-120b.
gpt-oss-120b vs MAI-1-preview
OpenAI · US | Microsoft · US · 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 MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai or ranked in the top 15 on lm arena at launch. Choose gpt-oss-120b if you need self-hosting or data privacy; MAI-1-preview if you want a managed API.
gpt-oss-120b (OpenAI) and MAI-1-preview (Microsoft) are two of the models people most often weigh against each other in 2026. 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. MAI-1-preview is microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. They diverge most on context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: gpt-oss-120b ships open weights you can self-host (hardware cost only, no per-token fee), while MAI-1-preview is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: 131K vs 128K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: MAI-1-preview is the newer model by about 23 days (released August 28, 2025), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
gpt-oss-120b
MAI-1-preview
Provider
OpenAI (US)
Microsoft (US)
Released
August 5, 2025
August 28, 2025
Context window
131K (~197 pages)
128K (~192 pages)
Price (in/out)
Open weight (self-host / free)
Not published
Open weight?
Yes — self-hostable
No — API only
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
Open weights make this possible at all — MAI-1-preview is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
MAI-1-preview is comparatively weak here — distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry
Agentic tool use, function calling, and code execution
gpt-oss-120b
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 — and its weights are open while MAI-1-preview is API-only.
Microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI
MAI-1-preview
gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models
Ranked in the top 15 on LM Arena at launch
MAI-1-preview
Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs — and it is the newer of the two.
Trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment
MAI-1-preview
MAI-1-preview lists trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment among its strengths; gpt-oss-120b does not.
Which should you pick?
Someone analysing very long documents or codebases
→ gpt-oss-120b
Larger 131K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ gpt-oss-120b
Open weights let you run it on your own hardware; MAI-1-preview is API-only.
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 microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai
→ MAI-1-preview
That is its strongest area.
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.
MAI-1-preview: where it fits
Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Released August 28, 2025 by Microsoft, it is built for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI, ranked in the top 15 on LM Arena at launch, trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment, and rolled into Copilot alongside OpenAI models, giving Microsoft a real second option.
Its trade-offs: a 'preview' release, not yet positioned as Microsoft's primary Copilot model, no public per-token API pricing - not sold as a standalone product, and distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry.
The bottom line for this matchup
The defining split here is open vs. closed. gpt-oss-120b gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. MAI-1-preview gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both gpt-oss-120b and MAI-1-preview 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.
Is gpt-oss-120b or MAI-1-preview better for coding?
Public SWE-Bench figures are not available for MAI-1-preview, 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 MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, gpt-oss-120b or MAI-1-preview?
gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while MAI-1-preview is API-metered at Not published. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Effectively neither — 131K vs 128K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both gpt-oss-120b and MAI-1-preview together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, MAI-1-preview 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 MAI-1-preview?
MAI-1-preview — released August 28, 2025, about 23 days 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.