Fugu Max vs Kimi K3.1 Pro
Sakana AI · Global | Moonshot AI · 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 Kimi K3.1 Pro for sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base or terminal-bench 4.0 of 65.7% (moonshot) and 67% as measured by artificial analysis.
Fugu Max (Sakana AI) and Kimi K3.1 Pro (Moonshot AI) 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. Kimi K3.1 Pro is moonshot's October 23, 2026 post-training upgrade to Kimi K3 - a 2.8T-parameter MoE at $2/$10 with open weights promised by November 4. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Context window: 1M tokens vs 1M tokens — 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: Kimi K3.1 Pro is the newer model by about 43 days (released October 23, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Fugu Max | Kimi K3.1 Pro |
|---|---|---|
| Provider | Sakana AI (Global) | Moonshot AI (China) |
| Released | September 10, 2026 | October 23, 2026 |
| Context window | 1M tokens (~1,500 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | $2/$6 per 1M tokens | $2/$10 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
Kimi K3.1 Pro is comparatively weak here — very high output-token use: roughly 150M output tokens across the Artificial Analysis index
1M-token context window at $2/$6 per million tokens
Fugu Max
Fugu Max lists 1M-token context window at $2/$6 per million tokens among its strengths; Kimi K3.1 Pro does not.
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; Kimi K3.1 Pro does not.
Sparse MoE with 2.8T total and about 104B active parameters, post-trained from the Kimi K3 base
Kimi K3.1 Pro
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
Terminal-Bench 4.0 of 65.7% (Moonshot) and 67% as measured by Artificial Analysis
Kimi K3.1 Pro
Moonshot's October 23, 2026 post-training upgrade to Kimi K3 - a 2.8T-parameter MoE at $2/$10 with open weights promised by November 4 — and it is the newer of the two.
Artificial Analysis Intelligence Index of 55, second only to Claude Opus 5.5 (58) among the models AI Weekly lists
Kimi K3.1 Pro
Kimi K3.1 Pro lists artificial Analysis Intelligence Index of 55, second only to Claude Opus 5.5 (58) among the models AI Weekly lists among its strengths; Fugu Max does not.
Which should you pick?
Someone analysing very long documents or codebases
→ Kimi K3.1 Pro
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 sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base
→ Kimi K3.1 Pro
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.
Kimi K3.1 Pro: where it fits
Moonshot's October 23, 2026 post-training upgrade to Kimi K3 - a 2.8T-parameter MoE at $2/$10 with open weights promised by November 4. Released October 23, 2026 by Moonshot AI, it is built for sparse MoE with 2.8T total and about 104B active parameters, post-trained from the Kimi K3 base, terminal-Bench 4.0 of 65.7% (Moonshot) and 67% as measured by Artificial Analysis, artificial Analysis Intelligence Index of 55, second only to Claude Opus 5.5 (58) among the models AI Weekly lists, and standard API price cut by a third versus K3 to $2/$10 per million tokens (Highspeed tier $4/$20).
Its trade-offs: weights promised by November 4, 2026 and not confirmed public as of November 3; license terms not yet disclosed, very high output-token use: roughly 150M output tokens across the Artificial Analysis index, self-hosting is impractical - about 1.4 TB of raw weights even at 4-bit, and most benchmarks are internal or use differing harnesses; no SWE-bench Verified figure published. At $2 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Fugu Max and Kimi K3.1 Pro overlap enough that the right pick depends on your specific job. Kimi K3.1 Pro 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%, Kimi K3.1 Pro for sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Fugu Max and Kimi K3.1 Pro 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 Kimi K3.1 Pro 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 Kimi K3.1 Pro leans toward sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Max or Kimi K3.1 Pro?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Effectively neither — 1M tokens vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Fugu Max and Kimi K3.1 Pro together?
Yes — a multi-model platform like LumiChats gives you Fugu Max, Kimi K3.1 Pro 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 Kimi K3.1 Pro?
Kimi K3.1 Pro — released October 23, 2026, about 43 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.