Fugu Ultra vs Claude Opus 4.8 vs GPT-5.4: Which $5/M Model Is Best for Coding?

The $5 Input Tier

A cluster of frontier models now price at or near $5 per million input tokens. This is the tier below the ultra-premium Claude Fable 5 and Mythos 5 ($10 input) but above the balanced tier (Claude Sonnet 4.6 at $3, GPT-5.4 at $2.50). For AI coding work, this tier represents the premium option where you're paying for reasoning quality and reliability on hard problems.

Three models are direct comparisons here:

GPT-5.4 is technically half-price in this comparison ($2.50 input, $15 output), but we include it because for many coding tasks it is the practical alternative to the true $5 input models.

Output Cost: The Critical Variable

For AI coding agents, output tokens typically account for 25–45% of total cost (input tokens dominate due to context accumulation). But at this price tier, the output rate spread — $15 vs $25 vs $30 per million — creates meaningful cost differences on large projects.

For a large project (50,000 LOC, CLI agent, production quality), our estimator puts total output tokens around 60M. The output cost difference:

Claude Opus 4.8's $25 output rate gives it a $300 cost advantage over Fugu Ultra and GPT-5.5 on the same large project. GPT-5.4 at $15 output is the most cost-efficient if the quality is sufficient.

Context Window: Who Needs 1M Tokens?

Fugu Ultra's 1M context window is its headline differentiator — but most AI coding workflows don't use more than 200K tokens per turn in practice. Claude Code and Cursor typically cap effective context at 150K–200K tokens per call due to performance and latency considerations, even when the model supports more.

The use case where Fugu Ultra's context advantage is real: ingesting an entire large monorepo in a single call for analysis, code review, or documentation generation. If you're doing that kind of bulk-codebase work, the 1M window eliminates chunking overhead. But above 272K tokens, Fugu Ultra's long-context rate ($10 input, $45 output) doubles the cost — which makes it the most expensive option at scale.

The Verdict: When to Use Each

Claude Opus 4.8: Best default for premium-tier coding work. Cheapest output at $25/M in this tier. Strong ecosystem integration with Claude Code. Predictable prompt caching behavior. The go-to if you're already on Anthropic's platform.

GPT-5.4: Best value in this comparison at $2.50/$15. If GPT-5.4 quality is sufficient for your project (it typically is for well-scoped tasks), the cost advantage over Opus 4.8 is 45–50% lower. Use this before defaulting to $5 input models.

Fugu Ultra: Best for bulk single-call codebase analysis at standard context lengths (≤272K), or if you need provider diversity (Japanese lab, non-US infrastructure for compliance). More expensive than Claude Opus 4.8 in every standard-context coding scenario.

GPT-5.5: Identical price to Fugu Ultra but with better ecosystem integration and longer evaluation history. Unless you specifically need Sakana's API, GPT-5.5 is the better default at the same price point.