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 Llama 4 Maverick for open weights, 1m context or strong image + text understanding. Choose Llama 4 Maverick if you need self-hosting or data privacy; Fugu Max if you want a managed API.
Fugu Max (Sakana AI) and Llama 4 Maverick (Meta) 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. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Llama 4 Maverick 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: 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 17 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Fugu Max
Llama 4 Maverick
Provider
Sakana AI (Global)
Meta (US)
Released
September 10, 2026
April 2025
Context window
1M tokens (~1,500 pages)
1M (~1,500 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, 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 — 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 — Fugu Max lists 1M-token context window at $2/$6 per million tokens among its strengths; Llama 4 Maverick 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; Llama 4 Maverick does not.
Open weights, 1M context: Llama 4 Maverick — Open weights make this possible at all — Fugu Max is API-only, so it cannot leave the vendor's servers.
Strong image + text understanding: Llama 4 Maverick — Meta's open-weight 1M-context multimodal model for self-hosted deployments — and its weights are open while Fugu Max is API-only.
Self-hostable: Llama 4 Maverick — Llama 4 Maverick lists self-hostable among its strengths; Fugu Max does not.
Lowest cost at scale: Llama 4 Maverick — Its weights are open, so at volume you pay for your own hardware instead of Fugu Max's $2/$6 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Llama 4 Maverick — At Open weight (self-host / free) it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: Llama 4 Maverick — 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 weights, 1m context: Llama 4 Maverick — 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.
Llama 4 Maverick: where it fits
Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.
Its trade-offs: needs serious hardware to self-host, and trails closed frontier on reasoning. 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. Llama 4 Maverick 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 Llama 4 Maverick 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 Llama 4 Maverick leans toward open weights, 1m context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Max or Llama 4 Maverick?
Llama 4 Maverick 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?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Fugu Max and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you Fugu Max, Llama 4 Maverick 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 Llama 4 Maverick?
Fugu Max — released September 10, 2026, about 17 months after Llama 4 Maverick.
Fugu Max vs Llama 4 Maverick
Sakana AI · Global | Meta · 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 Llama 4 Maverick for open weights, 1m context or strong image + text understanding. Choose Llama 4 Maverick if you need self-hosting or data privacy; Fugu Max if you want a managed API.
Fugu Max (Sakana AI) and Llama 4 Maverick (Meta) 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. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: Llama 4 Maverick 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: 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 17 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Fugu Max
Llama 4 Maverick
Provider
Sakana AI (Global)
Meta (US)
Released
September 10, 2026
April 2025
Context window
1M tokens (~1,500 pages)
1M (~1,500 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, 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
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
Fugu Max lists 1M-token context window at $2/$6 per million tokens among its strengths; Llama 4 Maverick 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; Llama 4 Maverick does not.
Open weights, 1M context
Llama 4 Maverick
Open weights make this possible at all — Fugu Max is API-only, so it cannot leave the vendor's servers.
Strong image + text understanding
Llama 4 Maverick
Meta's open-weight 1M-context multimodal model for self-hosted deployments — and its weights are open while Fugu Max is API-only.
Self-hostable
Llama 4 Maverick
Llama 4 Maverick lists self-hostable among its strengths; Fugu Max does not.
Lowest cost at scale
Llama 4 Maverick
Its weights are open, so at volume you pay for your own hardware instead of Fugu Max's $2/$6 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Llama 4 Maverick
At Open weight (self-host / free) it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ Llama 4 Maverick
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 weights, 1m context
→ Llama 4 Maverick
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.
Llama 4 Maverick: where it fits
Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.
Its trade-offs: needs serious hardware to self-host, and trails closed frontier on reasoning. 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. Llama 4 Maverick 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 Llama 4 Maverick 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.
Is Fugu Max or Llama 4 Maverick 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 Llama 4 Maverick leans toward open weights, 1m context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Max or Llama 4 Maverick?
Llama 4 Maverick 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?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Fugu Max and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you Fugu Max, Llama 4 Maverick 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 Llama 4 Maverick?
Fugu Max — released September 10, 2026, about 17 months after Llama 4 Maverick.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.