Model comparison
GPT-5.3 Codex vs Sakana Fugu-Ultra
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.3 Codex #26 (Supported); Sakana Fugu-Ultra unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.3 Codex and Sakana Fugu-Ultra share 2 comparable benchmark results. 2 of 8 categories are comparable. 19 results are unique to GPT-5.3 Codex; 9 to Sakana Fugu-Ultra.
Updated July 23, 2026- Shared results
- 2
- GPT-5.3 Codex only
- 19
- Sakana Fugu-Ultra only
- 9
- Comparable categories
- 2 / 8
Treat this as a split decision. GPT-5.3 Codex makes more sense if coding is the priority; Sakana Fugu-Ultra is the better fit if agentic is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.3 Codex and Sakana Fugu-Ultra finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Sakana Fugu-Ultra gives you the larger context window at 1M, compared with 400K for GPT-5.3 Codex.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5.3 Codex | Δ | Sakana Fugu-Ultra |
|---|---|---|---|
| Agentic | GPT-5.3 Codex71.4 | Margin→ 10.7 | Sakana Fugu-Ultra82.1 |
| Coding | GPT-5.3 Codex67.2 | Margin← 2.7 | Sakana Fugu-Ultra64.5 |
| Reasoning | GPT-5.3 CodexNot measured | MarginNo overlap | Sakana Fugu-Ultra93.6 |
| Knowledge | GPT-5.3 CodexNot measured | MarginNo overlap | Sakana Fugu-Ultra95.5 |
| Multimodal | GPT-5.3 CodexNot measured | MarginNo overlap | Sakana Fugu-Ultra86.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Pro
CodingA 56.8%B 73.7%Winner: Sakana Fugu-UltraΔ 16.9SWE-bench Pro: GPT-5.3 Codex scored 56.8%; Sakana Fugu-Ultra scored 73.7%. Sakana Fugu-Ultra wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 77.3%B 82.1%Winner: Sakana Fugu-UltraΔ 4.8Terminal-Bench 2.0: GPT-5.3 Codex scored 77.3%; Sakana Fugu-Ultra scored 82.1%. Sakana Fugu-Ultra wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.3 Codex | Sakana Fugu-Ultra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.3 Codex$1.75 input / $14 output | Sakana Fugu-UltraNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.3 Codex79 tok/s | Sakana Fugu-UltraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.3 Codex88.26 s | Sakana Fugu-UltraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.3 Codex400K | Sakana Fugu-Ultra1M | Sakana Fugu-Ultra lists the larger context window. |
Benchmark Deep Dive
AgenticSakana Fugu-Ultra wins5 benchmarks
CodingGPT-5.3 Codex wins9 benchmarks
| Benchmark | GPT-5.3 Codex | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 85% | — | Not comparable |
| SWE-bench ProSource | 56.8% | 73.7% | Sakana Fugu-Ultra leads |
| SWE-RebenchSource | 58.2% | — | Not comparable |
| Vibe Code BenchSource | 61.77% | — | Not comparable |
| AA-SciCodeSource | 53.2% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 82.1% | Not comparable |
| LiveCodeBench v6Source | — | 93.2% | Not comparable |
| LiveCodeBench ProSource | — | 90.8% | Not comparable |
| SciCodeSource | — | 58.7% | Not comparable |
Reasoning3 benchmarks
Knowledge9 benchmarks
| Benchmark | GPT-5.3 Codex | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 44.3% | — | Not comparable |
| AA-GPQA DiamondSource | 91.5% | — | Not comparable |
| AA-HLESource | 39.9% | — | Not comparable |
| AA-Omniscience IndexSource | 9.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 51.8% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 86.9% | — | Not comparable |
| GPQASource | — | 95.5% | Not comparable |
| GPQA-DSource | — | 95.5% | Not comparable |
| HLE w/o toolsSource | — | 50% | Not comparable |
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.3 Codex | Sakana Fugu-Ultra | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, GPT-5.3 Codex or Sakana Fugu-Ultra?
GPT-5.3 Codex and Sakana Fugu-Ultra are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for coding, GPT-5.3 Codex or Sakana Fugu-Ultra?
GPT-5.3 Codex has the edge for coding in this comparison, averaging 67.2 versus 64.5. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.3 Codex or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the edge for agentic tasks in this comparison, averaging 82.1 versus 71.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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