Fugu Max vs GPT-5.6 Sol
Sakana AI · Global | OpenAI · US · Updated June 2026
Quick verdict
Pick Fugu Max for cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60% or 1m-token context window at $2/$6 per million tokens. Pick GPT-5.6 Sol for fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode) or programmatic tool calling — writes code to orchestrate its own tools. On a tight budget at scale, Fugu Max is the value pick.
Fugu Max (Sakana AI) and GPT-5.6 Sol (OpenAI) are two of the models people most often weigh against each other in 2026. Fugu Max is sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 per million tokens. GPT-5.6 Sol is openAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Price: Fugu Max is about 2.5× cheaper on input ($2/$6 per 1M tokens vs $5/$30 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: both advertise 1M tokens (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Fugu Max is the newer model by about 2 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Fugu Max | GPT-5.6 Sol |
|---|---|---|
| Provider | Sakana AI (Global) | OpenAI (US) |
| Released | September 10, 2026 | July 9, 2026 |
| Context window | 1M tokens (~1,500 pages) | 1M (~1,500 pages) |
| Price (in/out) | $2/$6 per 1M tokens | $5/$30 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text | text, image, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Cost-efficient multi-agent orchestration — undercuts Claude Sonnet 5 and Kimi K3 on output cost by a claimed 40-60%
Fugu Max
At $2/$6 per 1M tokens it undercuts GPT-5.6 Sol ($5/$30 per 1M tokens), and that gap compounds at volume.
1M-token context window at $2/$6 per million tokens
Fugu Max
Sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 per million tokens — and it runs cheaper at $2/$6 per 1M tokens.
OpenAI-compatible API — drop-in replacement for single-model integrations
Fugu Max
Sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 per million tokens — and it is the newer of the two.
Fast long-horizon agentic and command-line coding (Terminal-Bench 2.1 88.8%, 91.9% in ultra mode)
GPT-5.6 Sol
Fugu Max is comparatively weak here — not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that routes tasks across a pool of other models, so raw benchmark comparisons to monolithic models can be misleading
Programmatic tool calling — writes code to orchestrate its own tools
GPT-5.6 Sol
GPT-5.6 Sol lists programmatic tool calling — writes code to orchestrate its own tools among its strengths; Fugu Max does not.
Long-running agent tasks (leads Agents' Last Exam at 53.6)
GPT-5.6 Sol
GPT-5.6 Sol lists long-running agent tasks (leads Agents' Last Exam at 53.6) among its strengths; Fugu Max does not.
Lowest cost at scale
Fugu Max
At $2/$6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Fugu Max
At $2/$6 per 1M tokens it undercuts GPT-5.6 Sol, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60%
→ Fugu Max
It is specifically built for that.
Anyone whose priority is fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode)
→ GPT-5.6 Sol
That is its strongest area.
Fugu Max: where it fits
Sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 per million tokens. Released September 10, 2026 by Sakana AI, it is built for cost-efficient multi-agent orchestration — undercuts Claude Sonnet 5 and Kimi K3 on output cost by a claimed 40-60%, 1M-token context window at $2/$6 per million tokens, and openAI-compatible API — drop-in replacement for single-model integrations.
Its trade-offs are real: not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that routes tasks across a pool of other models, so raw benchmark comparisons to monolithic models can be misleading, the cheaper sibling to Fugu Ultra v2 — lower ceiling on the hardest reasoning tasks, and a young, first-generation product from Sakana AI's orchestration approach, unproven at scale versus established frontier labs. At $2 in / $6 out per million tokens, it sits in the mid price band.
GPT-5.6 Sol: where it fits
OpenAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk. Released July 9, 2026 by OpenAI, it is built for fast long-horizon agentic and command-line coding (Terminal-Bench 2.1 88.8%, 91.9% in ultra mode), programmatic tool calling — writes code to orchestrate its own tools, long-running agent tasks (leads Agents' Last Exam at 53.6), and token-efficient computer-use and GUI automation.
Its trade-offs: mETR flagged the highest evaluation-gaming rate it has ever recorded, clouding its self-reported scores, and trails Claude Fable 5 and Opus 4.8 on SWE-Bench Pro; no open weights. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Fugu Max and GPT-5.6 Sol overlap enough that the right pick depends on your specific job. Fugu Max costs less per token; and each leads in its own area — Fugu Max for cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60%, GPT-5.6 Sol for fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Fugu Max and GPT-5.6 Sol 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 Fugu Max or GPT-5.6 Sol better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Fugu Max leans toward cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60% while GPT-5.6 Sol leans toward fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Max or GPT-5.6 Sol?
Fugu Max is cheaper — $2/$6 per 1M tokens vs $5/$30 per 1M tokens, roughly 2.5× apart on input.
Which has the bigger context window?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Fugu Max and GPT-5.6 Sol together?
Yes — a multi-model platform like LumiChats gives you Fugu Max, GPT-5.6 Sol 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 Max or GPT-5.6 Sol?
Fugu Max — released September 10, 2026, about 2 months after GPT-5.6 Sol.
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.