Pick Fugu Ultra v2.0 for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark or claims to outperform flagship models like gpt-6 astra and claude fable 5.1 despite its underlying orchestration pool reportedly excluding both of them. Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Choose gpt-oss-120b if you need self-hosting or data privacy; Fugu Ultra v2.0 if you want a managed API.
Fugu Ultra v2.0 (Sakana AI) and gpt-oss-120b (OpenAI) are two of the models people most often weigh against each other in 2026. Fugu Ultra v2.0 is sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. 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. They diverge most on price, 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 Fugu Ultra v2.0 is API-metered at $5/$30 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Fugu Ultra v2.0 holds 7.6× more — 1M tokens (~1,500 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: Fugu Ultra v2.0 is the newer model by about 13 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Fugu Ultra v2.0
gpt-oss-120b
Provider
Sakana AI (Global)
OpenAI (US)
Released
September 10, 2026
August 5, 2025
Context window
1M tokens (~1,500 pages)
131K (~197 pages)
Price (in/out)
$5/$30 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text
text, code
SWE-Bench Verified
Not published
62.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark: Fugu Ultra v2.0 — Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens — and it carries the larger 1M tokens context.
Claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them: Fugu Ultra v2.0 — gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models
1M-token context window: Fugu Ultra v2.0 — Its 1M tokens window holds about 7.6× more than gpt-oss-120b's 131K in a single prompt.
Self-hostable on a single 80GB H100 GPU via MXFP4: gpt-oss-120b — Open weights make this possible at all — Fugu Ultra v2.0 is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high): 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 Fugu Ultra v2.0 is API-only.
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; Fugu Ultra v2.0 does not.
Lowest cost at scale: gpt-oss-120b — Its weights are open, so at volume you pay for your own hardware instead of Fugu Ultra v2.0's $5/$30 per 1M tokens.
Largest single-prompt input: Fugu Ultra v2.0 — Its 1M tokens window is about 7.6× larger than gpt-oss-120b's 131K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: gpt-oss-120b — At Open weight (self-host / free) it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Fugu Ultra v2.0 — Larger 1M tokens 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; Fugu Ultra v2.0 is API-only.
Anyone whose priority is sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark: Fugu Ultra v2.0 — 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.
Fugu Ultra v2.0: where it fits
Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. Released September 10, 2026 by Sakana AI, it is built for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark, claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them, and 1M-token context window.
Its trade-offs are real: not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that dynamically routes tasks across a pool of other models, so head-to-head benchmark framing against monolithic frontier models should be read skeptically, pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens, and benchmark comparisons against GPT-6 Astra and Claude Fable 5.1 are Sakana's own self-reported figures, not independently verified head-to-head scores. At $5 in / $30 out per million tokens, it sits in the premium price band.
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
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. Fugu Ultra v2.0 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 Fugu Ultra v2.0 or gpt-oss-120b better for coding?
Public SWE-Bench figures are not available for Fugu Ultra v2.0, so the honest test is your own repository — run an identical real bug through both. By design, Fugu Ultra v2.0 leans toward sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark 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, Fugu Ultra v2.0 or gpt-oss-120b?
gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Fugu Ultra v2.0 is API-metered at $5/$30 per 1M tokens. 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?
Fugu Ultra v2.0 — 1M tokens vs 131K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Fugu Ultra v2.0 and gpt-oss-120b together?
Yes — a multi-model platform like LumiChats gives you Fugu Ultra v2.0, 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, Fugu Ultra v2.0 or gpt-oss-120b?
Fugu Ultra v2.0 — released September 10, 2026, about 13 months after gpt-oss-120b.
Fugu Ultra v2.0 vs gpt-oss-120b
Sakana AI · Global | OpenAI · US · Updated June 2026
Quick verdict
Pick Fugu Ultra v2.0 for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark or claims to outperform flagship models like gpt-6 astra and claude fable 5.1 despite its underlying orchestration pool reportedly excluding both of them. Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Choose gpt-oss-120b if you need self-hosting or data privacy; Fugu Ultra v2.0 if you want a managed API.
Fugu Ultra v2.0 (Sakana AI) and gpt-oss-120b (OpenAI) are two of the models people most often weigh against each other in 2026. Fugu Ultra v2.0 is sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. 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. They diverge most on price, 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 Fugu Ultra v2.0 is API-metered at $5/$30 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Fugu Ultra v2.0 holds 7.6× more — 1M tokens (~1,500 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: Fugu Ultra v2.0 is the newer model by about 13 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Fugu Ultra v2.0
gpt-oss-120b
Provider
Sakana AI (Global)
OpenAI (US)
Released
September 10, 2026
August 5, 2025
Context window
1M tokens (~1,500 pages)
131K (~197 pages)
Price (in/out)
$5/$30 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text
text, code
SWE-Bench Verified
Not published
62.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark
Fugu Ultra v2.0
Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens — and it carries the larger 1M tokens context.
Claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them
Fugu Ultra v2.0
gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models
1M-token context window
Fugu Ultra v2.0
Its 1M tokens window holds about 7.6× more than gpt-oss-120b's 131K in a single prompt.
Self-hostable on a single 80GB H100 GPU via MXFP4
gpt-oss-120b
Open weights make this possible at all — Fugu Ultra v2.0 is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high)
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 Fugu Ultra v2.0 is API-only.
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; Fugu Ultra v2.0 does not.
Lowest cost at scale
gpt-oss-120b
Its weights are open, so at volume you pay for your own hardware instead of Fugu Ultra v2.0's $5/$30 per 1M tokens.
Largest single-prompt input
Fugu Ultra v2.0
Its 1M tokens window is about 7.6× larger than gpt-oss-120b's 131K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ gpt-oss-120b
At Open weight (self-host / free) it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Fugu Ultra v2.0
Larger 1M tokens 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; Fugu Ultra v2.0 is API-only.
Anyone whose priority is sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark
→ Fugu Ultra v2.0
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.
Fugu Ultra v2.0: where it fits
Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. Released September 10, 2026 by Sakana AI, it is built for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark, claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them, and 1M-token context window.
Its trade-offs are real: not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that dynamically routes tasks across a pool of other models, so head-to-head benchmark framing against monolithic frontier models should be read skeptically, pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens, and benchmark comparisons against GPT-6 Astra and Claude Fable 5.1 are Sakana's own self-reported figures, not independently verified head-to-head scores. At $5 in / $30 out per million tokens, it sits in the premium price band.
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
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. Fugu Ultra v2.0 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 Fugu Ultra v2.0 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.
Is Fugu Ultra v2.0 or gpt-oss-120b better for coding?
Public SWE-Bench figures are not available for Fugu Ultra v2.0, so the honest test is your own repository — run an identical real bug through both. By design, Fugu Ultra v2.0 leans toward sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark 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, Fugu Ultra v2.0 or gpt-oss-120b?
gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Fugu Ultra v2.0 is API-metered at $5/$30 per 1M tokens. 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?
Fugu Ultra v2.0 — 1M tokens vs 131K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Fugu Ultra v2.0 and gpt-oss-120b together?
Yes — a multi-model platform like LumiChats gives you Fugu Ultra v2.0, 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, Fugu Ultra v2.0 or gpt-oss-120b?
Fugu Ultra v2.0 — released September 10, 2026, about 13 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.