AI Models · Paid vs Paid

SAFugu Ultra v2 Paid vs Claude Haiku 4.5 Paid

Fugu Ultra v2 vs Claude Haiku 4.5 compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

SAFugu Ultra v2PaidSakana AI
$5 /M input
$30 /M outputManaged API (no infra to run)
TypeProprietary
Context window1M tokens
MultimodalYes
Self-hostNo
Claude Haiku 4.5PaidAnthropic
$1 /M input
$5 /M outputManaged API (no infra to run)
TypeProprietary
Context window200K tokens
MultimodalYes
Self-hostNo
Choose Claude Haiku 4.5 for the lower output price ($5/M vs $30/M). Choose Fugu Ultra v2 if you need the larger 1M context window.

Fugu Ultra v2 vs Claude Haiku 4.5 specs

SpecFugu Ultra v2Claude Haiku 4.5Winner
MakerSakana AIAnthropic
TypeProprietaryProprietary
Context window1M tokens200K tokensSAFugu Ultra v2
Input price$5/M$1/MClaude Haiku 4.5
Output price$30/M$5/MClaude Haiku 4.5
Vision / multimodalYesYes= Tie
Tool / function callingYesYes= Tie
Self-hostableNo (API only)No (API only)
LicenseProprietaryProprietary

Price gap & when to choose each

6.0×cheaper per output token

Claude Haiku 4.5 is ~6.0× cheaper than Fugu Ultra v2 on output tokens ($5 vs $30 per M tokens).

SAChoose Fugu Ultra v2 if…
  • You want frontier performance through a managed API
  • You need the longer 1M context window
  • You value reliability & ecosystem
  • You don't want to manage infrastructure
Choose Claude Haiku 4.5 if…
  • You want frontier performance through a managed API
  • You want the lower output price
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityFugu Ultra v2Claude Haiku 4.5
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Fugu Ultra v2 vs Claude Haiku 4.5

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

Fugu Ultra v2
Claude Haiku 4.5
Intelligence index
17.6
Coding index
43.9
Math index
83.7
GPQA
67.2%
MMLU-Pro
76%
Humanity's Last Exam
10.4%
Long Context Reasoning
74.3%
LiveCodeBench
61.5%
SciCode
42.2%
AIME 2025
83.7%
IFBench
54.3%
τ²-Bench
54.7%
τ-Bench Banking
9.3%
Terminal-Bench
44.2%
Terminal-Bench Hard
27.3%
Speed
105.5 tok/s
Latency
12.43s
Intelligence per $
8.8

Benchmark data by Artificial Analysis.

How Fugu Ultra v2 and Claude Haiku 4.5 score

🤝 Neck and neck on these criteria (3.1 vs 3.1 / 5).
CriterionFugu Ultra v2Claude Haiku 4.5
Cost-efficiency3.04.0
Context window5.04.0
Openness1.51.5
Self-hosting1.01.0
Multimodality5.05.0

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

Fugu Ultra v2 Paid

Sakana AI · Proprietary

Fugu Ultra v2 is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to...

Claude Haiku 4.5 Paid

Anthropic · Proprietary

Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...

Other models in these families

These variants are tracked but not compared here — one page per family keeps the comparison readable.

Other variants tracked
Claude Haiku 4.5 (batch)Claude 3 Haiku

Frequently asked questions

Fugu Ultra v2 vs Claude Haiku 4.5 — which is cheaper?

Claude Haiku 4.5 is cheaper on output ($5/M vs $30/M).

Which has the larger context window?

Fugu Ultra v2 offers the larger context window (1M tokens).

Fugu Ultra v2 vs Claude Haiku 4.5 — which should I pick in 2026?

Choose Claude Haiku 4.5 for the lower output price ($5/M vs $30/M). Choose Fugu Ultra v2 if you need the larger 1M context window.

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