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 Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. Choose Hunyuan Hy3 if you need self-hosting or data privacy; Fugu Max if you want a managed API.
Fugu Max (Sakana AI) and Hunyuan Hy3 (Tencent) 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. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Hunyuan Hy3 ships open weights you can self-host (hardware cost only, no per-token fee), while Fugu Max is API-metered at $2/$6 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Fugu Max holds 3.9× more — 1M tokens (~1,500 pages) vs 256K (~384 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 Max is the newer model by about 2 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Fugu Max
Hunyuan Hy3
Provider
Sakana AI (Global)
Tencent (China)
Released
September 10, 2026
July 6, 2026
Context window
1M tokens (~1,500 pages)
256K (~384 pages)
Price (in/out)
$2/$6 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
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 — 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.
1M-token context window at $2/$6 per million tokens: Fugu Max — Its 1M tokens window holds about 3.9× more than Hunyuan Hy3's 256K 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 is the newer of the two.
Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost: Hunyuan Hy3 — Fugu Max is comparatively weak here — the cheaper sibling to Fugu Ultra v2 — lower ceiling on the hardest reasoning tasks
Runs a 295B model at the cost of a 21B — only 21B parameters active per token: Hunyuan Hy3 — 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
Clean, unrestricted Apache-2.0 license with no geographic carve-out: Hunyuan Hy3 — A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and its weights are open while Fugu Max is API-only.
Lowest cost at scale: Hunyuan Hy3 — Its weights are open, so at volume you pay for your own hardware instead of Fugu Max's $2/$6 per 1M tokens.
Largest single-prompt input: Fugu Max — Its 1M tokens window is about 3.9× larger than Hunyuan Hy3's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Hunyuan Hy3 — At Open weight (self-host / free) it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Fugu Max — Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs: Hunyuan Hy3 — 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 frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost: Hunyuan Hy3 — 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.
Hunyuan Hy3: where it fits
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.
Its trade-offs: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. 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. Hunyuan Hy3 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.
Frequently asked questions
Is Fugu Max or Hunyuan Hy3 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 Hunyuan Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Max or Hunyuan Hy3?
Hunyuan Hy3 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?
Fugu Max — 1M tokens vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Fugu Max and Hunyuan Hy3 together?
Yes — a multi-model platform like LumiChats gives you Fugu Max, Hunyuan Hy3 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 Hunyuan Hy3?
Fugu Max — released September 10, 2026, about 2 months after Hunyuan Hy3.
Fugu Max vs Hunyuan Hy3
Sakana AI · Global | Tencent · 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 Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. Choose Hunyuan Hy3 if you need self-hosting or data privacy; Fugu Max if you want a managed API.
Fugu Max (Sakana AI) and Hunyuan Hy3 (Tencent) 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. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. 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: Hunyuan Hy3 ships open weights you can self-host (hardware cost only, no per-token fee), while Fugu Max is API-metered at $2/$6 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Fugu Max holds 3.9× more — 1M tokens (~1,500 pages) vs 256K (~384 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 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
Hunyuan Hy3
Provider
Sakana AI (Global)
Tencent (China)
Released
September 10, 2026
July 6, 2026
Context window
1M tokens (~1,500 pages)
256K (~384 pages)
Price (in/out)
$2/$6 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
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
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.
1M-token context window at $2/$6 per million tokens
Fugu Max
Its 1M tokens window holds about 3.9× more than Hunyuan Hy3's 256K 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 is the newer of the two.
Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost
Hunyuan Hy3
Fugu Max is comparatively weak here — the cheaper sibling to Fugu Ultra v2 — lower ceiling on the hardest reasoning tasks
Runs a 295B model at the cost of a 21B — only 21B parameters active per token
Hunyuan Hy3
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
Clean, unrestricted Apache-2.0 license with no geographic carve-out
Hunyuan Hy3
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and its weights are open while Fugu Max is API-only.
Lowest cost at scale
Hunyuan Hy3
Its weights are open, so at volume you pay for your own hardware instead of Fugu Max's $2/$6 per 1M tokens.
Largest single-prompt input
Fugu Max
Its 1M tokens window is about 3.9× larger than Hunyuan Hy3's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Hunyuan Hy3
At Open weight (self-host / free) it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Fugu Max
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Hunyuan Hy3
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 frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost
→ Hunyuan Hy3
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.
Hunyuan Hy3: where it fits
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.
Its trade-offs: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. 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. Hunyuan Hy3 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 Hunyuan Hy3 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.
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 Hunyuan Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Max or Hunyuan Hy3?
Hunyuan Hy3 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?
Fugu Max — 1M tokens vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Fugu Max and Hunyuan Hy3 together?
Yes — a multi-model platform like LumiChats gives you Fugu Max, Hunyuan Hy3 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 Hunyuan Hy3?
Fugu Max — released September 10, 2026, about 2 months after Hunyuan Hy3.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.