Pick Fugu Ultra v2.0 for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark or claims to outperform flagship models like gpt-6 astra and claude fable 5.1 despite its underlying orchestration pool reportedly excluding both of them. Pick Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) or subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck. On a tight budget at scale, Muse Spark 1.1 is the value pick.
Fugu Ultra v2.0 (Sakana AI) and Muse Spark 1.1 (Meta) are two of the models people most often weigh against each other in 2026. Fugu Ultra v2.0 is sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Muse Spark 1.1 is about 4× cheaper on input ($1.25/$4.25 per 1M tokens vs $5/$30 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: 1M tokens vs 1M — 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: Fugu Ultra v2.0 is the newer model by about 2 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Fugu Ultra v2.0
Muse Spark 1.1
Provider
Sakana AI (Global)
Meta (US)
Released
September 10, 2026
July 9, 2026
Context window
1M tokens (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
$5/$30 per 1M tokens
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
54.1%
Who wins what
Sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark: Fugu Ultra v2.0 — Muse Spark 1.1 is comparatively weak here — not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark
Claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them: Fugu Ultra v2.0 — Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens — and it is the newer of the two.
1M-token context window: Fugu Ultra v2.0 — Muse Spark 1.1 is comparatively weak here — the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0
Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported): Muse Spark 1.1 — At $1.25/$4.25 per 1M tokens it undercuts Fugu Ultra v2.0 ($5/$30 per 1M tokens), and that gap compounds at volume.
Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck: Muse Spark 1.1 — Fugu Ultra v2.0 is comparatively weak here — not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that dynamically routes tasks across a pool of other models, so head-to-head benchmark framing against monolithic frontier models should be read skeptically
Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported): Muse Spark 1.1 — Fugu Ultra v2.0 is comparatively weak here — benchmark comparisons against GPT-6 Astra and Claude Fable 5.1 are Sakana's own self-reported figures, not independently verified head-to-head scores
Lowest cost at scale: Muse Spark 1.1 — At $1.25/$4.25 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: Muse Spark 1.1 — At $1.25/$4.25 per 1M tokens it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Muse Spark 1.1 — Larger 1M window fits more in one prompt.
Anyone whose priority is sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark: Fugu Ultra v2.0 — It is specifically built for that.
Anyone whose priority is scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported): Muse Spark 1.1 — That is its strongest area.
Fugu Ultra v2.0: where it fits
Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. Released September 10, 2026 by Sakana AI, it is built for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark, claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them, and 1M-token context window.
Its trade-offs are real: not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that dynamically routes tasks across a pool of other models, so head-to-head benchmark framing against monolithic frontier models should be read skeptically, pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens, and benchmark comparisons against GPT-6 Astra and Claude Fable 5.1 are Sakana's own self-reported figures, not independently verified head-to-head scores. At $5 in / $30 out per million tokens, it sits in the premium price band.
Muse Spark 1.1: where it fits
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.
Its trade-offs: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Fugu Ultra v2.0 and Muse Spark 1.1 overlap enough that the right pick depends on your specific job. Muse Spark 1.1 costs less per token; Muse Spark 1.1 holds the larger context; and each leads in its own area — Fugu Ultra v2.0 for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark, Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Fugu Ultra v2.0 or Muse Spark 1.1 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 Ultra v2.0 leans toward sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark while Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Ultra v2.0 or Muse Spark 1.1?
Muse Spark 1.1 is cheaper — $5/$30 per 1M tokens vs $1.25/$4.25 per 1M tokens, roughly 4× apart on input.
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 Ultra v2.0 and Muse Spark 1.1 together?
Yes — a multi-model platform like LumiChats gives you Fugu Ultra v2.0, Muse Spark 1.1 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 Ultra v2.0 or Muse Spark 1.1?
Fugu Ultra v2.0 — released September 10, 2026, about 2 months after Muse Spark 1.1.
Fugu Ultra v2.0 vs Muse Spark 1.1
Sakana AI · Global | Meta · US · Updated June 2026
Quick verdict
Pick Fugu Ultra v2.0 for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark or claims to outperform flagship models like gpt-6 astra and claude fable 5.1 despite its underlying orchestration pool reportedly excluding both of them. Pick Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) or subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck. On a tight budget at scale, Muse Spark 1.1 is the value pick.
Fugu Ultra v2.0 (Sakana AI) and Muse Spark 1.1 (Meta) are two of the models people most often weigh against each other in 2026. Fugu Ultra v2.0 is sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Muse Spark 1.1 is about 4× cheaper on input ($1.25/$4.25 per 1M tokens vs $5/$30 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: 1M tokens vs 1M — 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: Fugu Ultra v2.0 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 Ultra v2.0
Muse Spark 1.1
Provider
Sakana AI (Global)
Meta (US)
Released
September 10, 2026
July 9, 2026
Context window
1M tokens (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
$5/$30 per 1M tokens
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
54.1%
Who wins what
Sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark
Fugu Ultra v2.0
Muse Spark 1.1 is comparatively weak here — not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark
Claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them
Fugu Ultra v2.0
Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens — and it is the newer of the two.
1M-token context window
Fugu Ultra v2.0
Muse Spark 1.1 is comparatively weak here — the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0
Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported)
Muse Spark 1.1
At $1.25/$4.25 per 1M tokens it undercuts Fugu Ultra v2.0 ($5/$30 per 1M tokens), and that gap compounds at volume.
Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck
Muse Spark 1.1
Fugu Ultra v2.0 is comparatively weak here — not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that dynamically routes tasks across a pool of other models, so head-to-head benchmark framing against monolithic frontier models should be read skeptically
Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported)
Muse Spark 1.1
Fugu Ultra v2.0 is comparatively weak here — benchmark comparisons against GPT-6 Astra and Claude Fable 5.1 are Sakana's own self-reported figures, not independently verified head-to-head scores
Lowest cost at scale
Muse Spark 1.1
At $1.25/$4.25 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
→ Muse Spark 1.1
At $1.25/$4.25 per 1M tokens it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark 1.1
Larger 1M window fits more in one prompt.
Anyone whose priority is sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark
→ Fugu Ultra v2.0
It is specifically built for that.
Anyone whose priority is scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported)
→ Muse Spark 1.1
That is its strongest area.
Fugu Ultra v2.0: where it fits
Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. Released September 10, 2026 by Sakana AI, it is built for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark, claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them, and 1M-token context window.
Its trade-offs are real: not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that dynamically routes tasks across a pool of other models, so head-to-head benchmark framing against monolithic frontier models should be read skeptically, pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens, and benchmark comparisons against GPT-6 Astra and Claude Fable 5.1 are Sakana's own self-reported figures, not independently verified head-to-head scores. At $5 in / $30 out per million tokens, it sits in the premium price band.
Muse Spark 1.1: where it fits
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.
Its trade-offs: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Fugu Ultra v2.0 and Muse Spark 1.1 overlap enough that the right pick depends on your specific job. Muse Spark 1.1 costs less per token; Muse Spark 1.1 holds the larger context; and each leads in its own area — Fugu Ultra v2.0 for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark, Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Fugu Ultra v2.0 and Muse Spark 1.1 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 Ultra v2.0 or Muse Spark 1.1 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 Ultra v2.0 leans toward sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark while Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Ultra v2.0 or Muse Spark 1.1?
Muse Spark 1.1 is cheaper — $5/$30 per 1M tokens vs $1.25/$4.25 per 1M tokens, roughly 4× apart on input.
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 Ultra v2.0 and Muse Spark 1.1 together?
Yes — a multi-model platform like LumiChats gives you Fugu Ultra v2.0, Muse Spark 1.1 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 Ultra v2.0 or Muse Spark 1.1?
Fugu Ultra v2.0 — released September 10, 2026, about 2 months after Muse Spark 1.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.