Model comparison
GPT-5.2-Codex vs Ornith-1.0-397B
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: GPT-5.2-Codex #58 (Supported); Ornith-1.0-397B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2-Codex and Ornith-1.0-397B share 0 comparable benchmark results. 0 of 8 categories are comparable. 15 results are unique to GPT-5.2-Codex; 7 to Ornith-1.0-397B.
Updated July 23, 2026- Shared results
- 0
- GPT-5.2-Codex only
- 15
- Ornith-1.0-397B only
- 7
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.2-Codex and Ornith-1.0-397B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GPT-5.2-Codex is priced at $1.75 input / $14.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ornith-1.0-397B. GPT-5.2-Codex has the larger context window at 400K, compared with 256K for Ornith-1.0-397B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.2-Codex | Ornith-1.0-397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2-Codex$1.75 input / $14 output | Ornith-1.0-397B$0 input / $0 output | Ornith-1.0-397B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.2-Codex123 tok/s | Ornith-1.0-397BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.2-Codex87.34 s | Ornith-1.0-397BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.2-Codex400K | Ornith-1.0-397B256K | GPT-5.2-Codex lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding7 benchmarks
| Benchmark | GPT-5.2-Codex | Ornith-1.0-397B | Result |
|---|---|---|---|
| Vibe Code BenchSource | 37.91% | — | Not comparable |
| AA-SciCodeSource | 54.6% | — | Not comparable |
| SWE-bench VerifiedSource | — | 82.4% | Not comparable |
| SWE-bench ProSource | — | 62.2% | Not comparable |
| SWE MultilingualSource | — | 78.9% | Not comparable |
| NL2RepoSource | — | 48.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 77.5% | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GPT-5.2-Codex | Ornith-1.0-397B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 40.1% | — | Not comparable |
| AA-GPQA DiamondSource | 89.9% | — | Not comparable |
| AA-HLESource | 33.5% | — | Not comparable |
| AA-Omniscience IndexSource | -2.5% | — | Not comparable |
| AA-Omniscience AccuracySource | 40.7% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 72.8% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | GPT-5.2-Codex | Ornith-1.0-397B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 76.3% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.2-Codex | Ornith-1.0-397B | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.6% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5.2-Codex and Ornith-1.0-397B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GPT-5.2-Codex and Ornith-1.0-397B today?
GPT-5.2-Codex: $1.75 input / $14.00 output per 1M tokens Ornith-1.0-397B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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