Fugu Max vs Grok 4.7

Sakana AI · Global  |  xAI · 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 Grok 4.7 for 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price or deepswe v1.1 (high effort): 71.0%, up from grok 4.6's 65.2%; cursorbench 4.0: 46.3%, up from 40.4%.

Fugu Max (Sakana AI) and Grok 4.7 (xAI) 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. Grok 4.7 is xAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.

Key differences at a glance

Side-by-side specs

SpecFugu MaxGrok 4.7
ProviderSakana AI (Global) xAI (US)
ReleasedSeptember 10, 2026 September 21, 2026
Context window1M tokens (~1,500 pages) 500K tokens (~750 pages)
Price (in/out)$2/$6 per 1M tokens $2/$6 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot 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

Grok 4.7 is comparatively weak here — reviewers note it arrives "late to the AI frontier party" against GPT-6 Astra, Claude Fable 5.1 and Opus 5.5, all shipped in the weeks just before it

1M-token context window at $2/$6 per million tokens

Fugu Max

Its 1M tokens window holds about 2× more than Grok 4.7's 500K tokens in a single prompt.

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 carries the larger 1M tokens context.

2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price

Grok 4.7

XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks — and it is the newer of the two.

DeepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%

Grok 4.7

Grok 4.7 lists deepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4% among its strengths; Fugu Max does not.

Trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems

Grok 4.7

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

Largest single-prompt input

Fugu Max

Its 1M tokens window is about 2× larger than Grok 4.7's 500K tokens, fitting roughly 1,500 pages in one prompt.

Which should you pick?

Someone analysing very long documents or codebases

Fugu Max

Larger 1M tokens window fits more in one prompt.

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 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price

Grok 4.7

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.

Grok 4.7: where it fits

XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. Released September 21, 2026 by xAI, it is built for 2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price, deepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%, trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems, and xAI's strongest safety guardrails to date, per the company.

Its trade-offs: release was delayed at least five times since late July 2026 before shipping, 500K context window trails several rivals now sitting at 1M+, and reviewers note it arrives "late to the AI frontier party" against GPT-6 Astra, Claude Fable 5.1 and Opus 5.5, all shipped in the weeks just before it. At $2 in / $6 out per million tokens, it sits in the mid price band.

The bottom line for this matchup

Fugu Max and Grok 4.7 overlap enough that the right pick depends on your specific job. Fugu Max holds the larger context; 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%, Grok 4.7 for 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price. Rather than crowning one, run the same hard task through both once and let the results decide.

Want both Fugu Max and Grok 4.7 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 pricing

Frequently asked questions

Is Fugu Max or Grok 4.7 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 Grok 4.7 leans toward 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Fugu Max or Grok 4.7?

They are priced almost identically, so cost will not decide between them.

Which has the bigger context window?

Fugu Max — 1M tokens vs 500K tokens, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Fugu Max and Grok 4.7 together?

Yes — a multi-model platform like LumiChats gives you Fugu Max, Grok 4.7 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 Grok 4.7?

Grok 4.7 — released September 21, 2026, about 11 days after Fugu Max.

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.