Model comparison
Celeris-1 vs GPT-5.4
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Celeris-1 unranked (Not scored); GPT-5.4 #8 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and GPT-5.4 share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Celeris-1; 54 to GPT-5.4.
Updated July 24, 2026- Shared results
- 0
- Celeris-1 only
- 1
- GPT-5.4 only
- 54
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if knowledge is the priority or you want the cheaper token bill; GPT-5.4 is the better fit if you need the larger 1.05M context window or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Celeris-1 and GPT-5.4 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.
GPT-5.4 is also the more expensive model on tokens at $2.50 input / $15.00 output per 1M tokens, versus $2.00 input / $6.00 output per 1M tokens for Celeris-1. That is roughly 2.5x on output cost alone. GPT-5.4 is the reasoning model in the pair, while Celeris-1 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-5.4 gives you the larger context window at 1.05M, compared with 8K for Celeris-1.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | GPT-5.4 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | GPT-5.4$2.5 input / $15 output | Celeris-1 has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | GPT-5.474 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | GPT-5.4151.79 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | GPT-5.41.05M | GPT-5.4 lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Celeris-1 | GPT-5.4 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 75.1% | Not comparable |
| CyberGymSource | — | 79.0% | Not comparable |
| BrowseCompSource | — | 82.7% | Not comparable |
| OSWorld-VerifiedSource | — | 75% | Not comparable |
| MCP AtlasSource | — | 70.6% | Not comparable |
| ToolathlonSource | — | 54.6% | Not comparable |
| τ²-bench resultsSource | — | 87.1% | Not comparable |
| Claw-EvalSource | — | 60.3% | Not comparable |
| DeepSearchQASource | — | 73.6% | Not comparable |
| AA Agentic IndexSource | — | 41.1% | Not comparable |
| APEX-Agents-AASource | — | 33.3% | Not comparable |
| GDPval-AASource | — | 44.7% | Not comparable |
| GDPval-AASource | — | 1395 | Not comparable |
| Gert LabsSource | — | 64.89% | Not comparable |
| ResearchClawBenchSource | — | 15.3% | Not comparable |
| JobBenchSource | — | 38.9% | Not comparable |
| ExploitGymSource | — | 6.0% | Not comparable |
Coding6 benchmarks
Reasoning4 benchmarks
KnowledgeCeleris-1 wins14 benchmarks
| Benchmark | Celeris-1 | GPT-5.4 | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | — | Not comparable |
| GPQASource | — | 92.8% | Not comparable |
| HLESource | — | 52.1% | Not comparable |
| HLE w/o toolsSource | — | 39.8% | Not comparable |
| GPQA-DSource | — | 92.8% | Not comparable |
| HealthBench HardSource | — | 40.1% | Not comparable |
| MedXpertQA (Text)Source | — | 59.6% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 51.4% | Not comparable |
| AA-GPQA DiamondSource | — | 92.0% | Not comparable |
| AA-HLESource | — | 41.6% | Not comparable |
| AA-Omniscience IndexSource | — | 5.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 50.0% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 88.6% | Not comparable |
| HealthBench ProfessionalSource | — | 48.1% | Not comparable |
Math2 benchmarks
Multimodal11 benchmarks
| Benchmark | Celeris-1 | GPT-5.4 | Result |
|---|---|---|---|
| MMMU-ProSource | — | 81.2% | Not comparable |
| OfficeQA ProSource | — | 53.2% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 82.1% | Not comparable |
| CharXivSource | — | 82.8% | Not comparable |
| ERQASource | — | 65.4% | Not comparable |
| SimpleVQASource | — | 61.1% | Not comparable |
| ScreenSpot ProSource | — | 85.4% | Not comparable |
| ZeroBenchSource | — | 41.0% | Not comparable |
| MedXpertQA (MM)Source | — | 77.1% | Not comparable |
| AA-MMMU-ProSource | — | 78.4% | Not comparable |
| Design Arena WebsiteSource | — | 1250 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | GPT-5.4 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 73.9% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or GPT-5.4?
Celeris-1 and GPT-5.4 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 knowledge tasks, Celeris-1 or GPT-5.4?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 57.6. GPT-5.4 stays close enough that the answer can still flip depending on your workload.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.