Fugu Max vs MiniMax M3

Sakana AI · Global  |  MiniMax · China · 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 MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context or native multimodal input — text, image and video. Choose MiniMax M3 if you need self-hosting or data privacy; Fugu Max if you want a managed API.

Fugu Max (Sakana AI) and MiniMax M3 (MiniMax) 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. MiniMax M3 is miniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. 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

Side-by-side specs

SpecFugu MaxMiniMax M3
ProviderSakana AI (Global) MiniMax (China)
ReleasedSeptember 10, 2026 May 31, 2026
Context window1M tokens (~1,500 pages) 1M (~1,573 pages)
Price (in/out)$2/$6 per 1M tokens $0.23/$0.96 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext text, image, video, 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

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.

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

Fugu Max

MiniMax M3 is comparatively weak here — price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M

OpenAI-compatible API — drop-in replacement for single-model integrations

Fugu Max

Fugu Max lists openAI-compatible API — drop-in replacement for single-model integrations among its strengths; MiniMax M3 does not.

Open-weight 428B MoE (~23B active per token) with a 1M-token context

MiniMax M3

Open weights make this possible at all — Fugu Max is API-only, so it cannot leave the vendor's servers.

Native multimodal input — text, image and video

MiniMax M3

MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing — and it runs cheaper at $0.23/$0.96 per 1M tokens.

Reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5

MiniMax M3

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

Lowest cost at scale

MiniMax M3

At $0.23/$0.96 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

MiniMax M3

At $0.23/$0.96 per 1M tokens it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

MiniMax M3

Larger 1M window fits more in one prompt.

A team with data-privacy or self-hosting needs

MiniMax M3

Open weights let you run it on your own hardware; Fugu Max is API-only.

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 open-weight 428b moe (~23b active per token) with a 1m-token context

MiniMax M3

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.

MiniMax M3: where it fits

MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. Released May 31, 2026 by MiniMax, it is built for open-weight 428B MoE (~23B active per token) with a 1M-token context, native multimodal input — text, image and video, reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5, and low entry pricing at $0.30/$1.20 per million up to 512K tokens.

Its trade-offs: price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M, miniMax's own reported 80.5 SWE-Bench Verified figure is vendor-stated, not independently verified, sWE-Bench Pro is a different, harder benchmark than SWE-Bench Verified, and newer than M2.7 but with less independent testing so far. At $0.23 in / $0.96 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

The defining split here is open vs. closed. MiniMax M3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Fugu Max 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 Max and MiniMax M3 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 MiniMax M3 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 MiniMax M3 leans toward open-weight 428b moe (~23b active per token) with a 1m-token context, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Fugu Max or MiniMax M3?

MiniMax M3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Fugu Max is API-metered at $2/$6 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?

Effectively neither — 1M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Fugu Max and MiniMax M3 together?

Yes — a multi-model platform like LumiChats gives you Fugu Max, MiniMax M3 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 MiniMax M3?

Fugu Max — released September 10, 2026, about 3 months after MiniMax M3.

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.