Model comparison
GPT-5.2-Codex vs Nemotron 3 Nano 30B
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.2-Codex #58 (Supported); Nemotron 3 Nano 30B #98 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2-Codex and Nemotron 3 Nano 30B share 11 comparable benchmark results. 0 of 8 categories are comparable. 4 results are unique to GPT-5.2-Codex; 4 to Nemotron 3 Nano 30B.
Updated July 20, 2026- Shared results
- 11
- GPT-5.2-Codex only
- 4
- Nemotron 3 Nano 30B only
- 4
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.2-Codex and Nemotron 3 Nano 30B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 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 Nemotron 3 Nano 30B. GPT-5.2-Codex has the larger context window at 400K, compared with 32K for Nemotron 3 Nano 30B.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.2-Codex | Nemotron 3 Nano 30B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2-Codex$1.75 input / $14 output | Nemotron 3 Nano 30B$0 input / $0 output | Nemotron 3 Nano 30B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.2-Codex123 tok/s | Nemotron 3 Nano 30B152 tok/s | Nemotron 3 Nano 30B has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-5.2-Codex87.34 s | Nemotron 3 Nano 30B1.90 s | Nemotron 3 Nano 30B reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-5.2-Codex400K | Nemotron 3 Nano 30B32K | GPT-5.2-Codex lists the larger context window. |
Benchmark Deep Dive
Agentic6 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GPT-5.2-Codex | Nemotron 3 Nano 30B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 40.1% | 14.2% | GPT-5.2-Codex leads |
| AA-GPQA DiamondSource | 89.9% | 75.7% | GPT-5.2-Codex leads |
| AA-HLESource | 33.5% | 10.2% | GPT-5.2-Codex leads |
| AA-Omniscience IndexSource | -2.5% | -51.6% | GPT-5.2-Codex leads |
| AA-Omniscience AccuracySource | 40.7% | 17.1% | GPT-5.2-Codex leads |
| AA-Omniscience Hallucination RateSource | 72.8% | 82.9% | GPT-5.2-Codex leads |
Multimodal1 benchmarks
| Benchmark | GPT-5.2-Codex | Nemotron 3 Nano 30B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 76.3% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.2-Codex | Nemotron 3 Nano 30B | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.6% | 71.1% | GPT-5.2-Codex leads |
Frequently Asked Questions (3)
Can I compare GPT-5.2-Codex and Nemotron 3 Nano 30B 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 Nemotron 3 Nano 30B today?
GPT-5.2-Codex: $1.75 input / $14.00 output per 1M tokens Nemotron 3 Nano 30B: $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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