Model comparison
DeepSeek V4 Pro (Max) vs GPT-5.2-Codex
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro (Max) unranked (Not scored); GPT-5.2-Codex #58 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro (Max) and GPT-5.2-Codex share 12 comparable benchmark results. 0 of 8 categories are comparable. 36 results are unique to DeepSeek V4 Pro (Max); 3 to GPT-5.2-Codex.
Updated July 23, 2026- Shared results
- 12
- DeepSeek V4 Pro (Max) only
- 36
- GPT-5.2-Codex only
- 3
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V4 Pro (Max) and GPT-5.2-Codex is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 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 $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro (Max). DeepSeek V4 Pro (Max) has the larger context window at 1M, compared with 400K for GPT-5.2-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 | DeepSeek V4 Pro (Max) | Δ | GPT-5.2-Codex |
|---|---|---|---|
| Agentic | DeepSeek V4 Pro (Max)74.5 | MarginNo overlap | GPT-5.2-CodexNot measured |
| Coding | DeepSeek V4 Pro (Max)70.9 | MarginNo overlap | GPT-5.2-CodexNot measured |
| Knowledge | DeepSeek V4 Pro (Max)60.1 | MarginNo overlap | GPT-5.2-CodexNot measured |
| Math | DeepSeek V4 Pro (Max)95.2 | MarginNo overlap | GPT-5.2-CodexNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro (Max) | GPT-5.2-Codex | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (Max)$0.435 input / $0.87 output | GPT-5.2-Codex$1.75 input / $14 output | DeepSeek V4 Pro (Max) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Pro (Max)Not available | GPT-5.2-Codex123 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (Max)Not available | GPT-5.2-Codex87.34 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (Max)1M | GPT-5.2-Codex400K | DeepSeek V4 Pro (Max) lists the larger context window. |
Benchmark Deep Dive
Agentic19 benchmarks
| Benchmark | DeepSeek V4 Pro (Max) | GPT-5.2-Codex | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 67.9% | — | Not comparable |
| BrowseCompSource | 83.4% | — | Not comparable |
| HLE w/ toolsSource | 48.2% | — | Not comparable |
| MCP AtlasSource | 73.6% | — | Not comparable |
| GDPval-AASource | 1307 | — | Not comparable |
| ToolathlonSource | 51.8% | — | Not comparable |
| AA Agentic IndexSource | 36.4% | — | Not comparable |
| APEX-Agents-AASource | 24.3% | — | Not comparable |
| τ²-bench resultsSource | 96.2% | 92.1% | DeepSeek V4 Pro (Max) leads |
| GDPval-AASource | 40.4% | — | Not comparable |
| AA BriefcaseSource | 932 | — | Not comparable |
| AA EnterpriseOps-GymSource | 40.4% | — | Not comparable |
| AA Harvey LABSource | 84.4% | — | Not comparable |
| AA ITBenchSource | 38.3% | — | Not comparable |
| AA Tau3 BankingSource | 25.8% | — | Not comparable |
| terminalBenchHardSource | 46.2% | — | Not comparable |
| aaTerminalBench21Source | 64% | — | Not comparable |
| Gert LabsSource | — | 51.79% | Not comparable |
| JobBenchSource | — | 26.0% | Not comparable |
Coding8 benchmarks
| Benchmark | DeepSeek V4 Pro (Max) | GPT-5.2-Codex | Result |
|---|---|---|---|
| CodeforcesSource | 3206.0 | — | Not comparable |
| SWE-bench VerifiedSource | 80.6% | — | Not comparable |
| SWE-bench ProSource | 55.4% | — | Not comparable |
| SWE MultilingualSource | 76.2% | — | Not comparable |
| Terminal-Bench 2.0Source | 67.9% | — | Not comparable |
| Vibe Code BenchSource | 49.93% | 37.91% | DeepSeek V4 Pro (Max) leads |
| AA Coding IndexSource | 59.4% | — | Not comparable |
| AA-SciCodeSource | 50.0% | 54.6% | GPT-5.2-Codex leads |
Reasoning4 benchmarks
Knowledge13 benchmarks
| Benchmark | DeepSeek V4 Pro (Max) | GPT-5.2-Codex | Result |
|---|---|---|---|
| MMLU-ProSource | 87.5% | — | Not comparable |
| SimpleQASource | 57.9% | — | Not comparable |
| Chinese-SimpleQASource | 84.4% | — | Not comparable |
| GPQASource | 90.1% | — | Not comparable |
| GPQA-DSource | 90.1% | — | Not comparable |
| HLESource | 37.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 44.3% | 40.1% | DeepSeek V4 Pro (Max) leads |
| AA-GPQA DiamondSource | 88.8% | 89.9% | GPT-5.2-Codex leads |
| AA-HLESource | 35.9% | 33.5% | DeepSeek V4 Pro (Max) leads |
| AA-Omniscience IndexSource | -10.0% | -2.5% | GPT-5.2-Codex leads |
| AA-Omniscience AccuracySource | 43.3% | 40.7% | DeepSeek V4 Pro (Max) leads |
| AA-Omniscience Hallucination RateSource | 94.0% | 72.8% | GPT-5.2-Codex leads |
| AA Openness IndexSource | 50.0% | — | Not comparable |
Math4 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro (Max) | GPT-5.2-Codex | Result |
|---|---|---|---|
| AA-IFBenchSource | 76.5% | 77.6% | GPT-5.2-Codex leads |
Frequently Asked Questions (3)
Can I compare DeepSeek V4 Pro (Max) and GPT-5.2-Codex 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 DeepSeek V4 Pro (Max) and GPT-5.2-Codex today?
DeepSeek V4 Pro (Max): $0.43 input / $0.87 output per 1M tokens GPT-5.2-Codex: $1.75 input / $14.00 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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