Model comparison
Chatgpt 4o Latest 20250326 vs DeepSeek-V3.2-Exp
Chatgpt 4o Latest 20250326 and DeepSeek-V3.2-Exp score almost the same on the Noometry Index (43.8 vs 44.3), so choose on price, context window or the category you care about most.
Last verified . 19 shared benchmarks.
DeepSeekSummary
- They share 19 benchmarks with published results for both. Chatgpt 4o Latest 20250326 scores higher in 3 categories and DeepSeek-V3.2-Exp in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3.2-Exp leads 51.7 to 39.2.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 75% for Chatgpt 4o Latest 20250326 and 52.2% for DeepSeek-V3.2-Exp.
- DeepSeek-V3.2-Exp has downloadable open weights; the other is API-only.
Side by side
| Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp | |
|---|---|---|
| Provider | OpenAI | DeepSeek |
| Noometry Index | 43.8 | 44.3 |
| Released | — | 2025-09-29 |
| Weights | Proprietary | Open |
| Context window | — | 164K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.26 |
| Output $ / M tokens | — | $0.38 |
| Results tracked | 21 | 49 |
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Category by category
Coding DeepSeek-V3.2-Exp leads
Chatgpt 4o Latest 20250326: 41.6 (#122), DeepSeek-V3.2-Exp: 46.5 (#65)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Coding | 1413 | 1454 |
| SWE-bench Verified (bash only) | — | 70% |
| Aider Polyglot | — | 74.2% |
| LMArena WebDev | — | 1362 |
| SWE-bench Multilingual | — | 59% |
| SciCode | — | 38.9% |
| WeirdML | — | 39.5% |
Agentic & Tool Use Not comparable
Chatgpt 4o Latest 20250326: —, DeepSeek-V3.2-Exp: 32.7 (#59)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| Terminal-Bench | — | 39.6% |
| APEX-Agents | — | 21.3% |
| Berkeley Function Calling Leaderboard | — | 56.7% |
| TheAgentCompany | — | 42.9% |
| Vending-Bench 2 | — | 1,034 |
Reasoning Chatgpt 4o Latest 20250326 leads
Chatgpt 4o Latest 20250326: 33.8 (#71), DeepSeek-V3.2-Exp: 22.1 (#208)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| Kagi LLM Benchmark | 75% | 52.2% |
| LMArena Hard Prompts | 1424 | 1434 |
| ARC-AGI-2 | — | 4% |
| NYT Connections (extended) | — | 36.7% |
| ARC-AGI-1 | — | 57% |
| CritPt | — | 2.9% |
| Chess Puzzles | — | 14% |
| Thematic Generalization | — | 65% |
| DTBench | — | 87.7% |
| LMCA | — | 29.1% |
| Epoch Capabilities Index | — | 146.27 |
Math DeepSeek-V3.2-Exp leads
Chatgpt 4o Latest 20250326: 38.6 (#134), DeepSeek-V3.2-Exp: 41.7 (#87)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Math | 1407 | 1435 |
| MathArena Final-Answer Competitions | — | 57.7% |
| OTIS Mock AIME 2024-2025 | — | 87.8% |
| ProofBench | — | 8% |
| FrontierMath (Feb 2025 set) | — | 22.1% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge DeepSeek-V3.2-Exp leads
Chatgpt 4o Latest 20250326: 39.2 (#137), DeepSeek-V3.2-Exp: 51.7 (#66)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Expert | 1401 | 1436 |
| GPQA Diamond | — | 83.4% |
| Confabulations | 16.6% | — |
| Vectara Hallucination Rate | — | 5.3% |
Multimodal Not comparable
Chatgpt 4o Latest 20250326: 39.6 (#58), DeepSeek-V3.2-Exp: —
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Vision | 1243 | — |
Multilingual Too close to call
Chatgpt 4o Latest 20250326: 52.9 (#76), DeepSeek-V3.2-Exp: 52.2 (#90)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Non-English | 1419 | 1409 |
| LMArena Chinese | 1457 | 1461 |
| LMArena French | 1446 | 1433 |
| LMArena German | 1423 | 1440 |
| LMArena Japanese | 1405 | 1374 |
| LMArena Korean | 1396 | 1371 |
| LMArena Russian | 1429 | 1424 |
| LMArena Spanish | 1434 | 1440 |
Instruction Following Too close to call
Chatgpt 4o Latest 20250326: 74.0 (#107), DeepSeek-V3.2-Exp: 74.5 (#93)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Instruction Following | 1403 | 1413 |
Long Context DeepSeek-V3.2-Exp leads
Chatgpt 4o Latest 20250326: 43.1 (#107), DeepSeek-V3.2-Exp: 47.6 (#16)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Longer Query | 1413 | 1428 |
| Fiction.LiveBench | — | 83.3% |
| CL-bench | — | 13.2% |
| CL-bench Life | — | 9.5% |
Writing & Preference Too close to call
Chatgpt 4o Latest 20250326: 62.6 (#72), DeepSeek-V3.2-Exp: 62.4 (#77)
| Benchmark | Chatgpt 4o Latest 20250326 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Text | 1429 | 1425 |
| LMArena Creative Writing | 1405 | 1403 |
| EQ-Bench Creative Writing | 1501 | 1515 |
| LMArena Multi-Turn | 1454 | 1427 |
Frequently asked questions
Is Chatgpt 4o Latest 20250326 better than DeepSeek-V3.2-Exp?
Chatgpt 4o Latest 20250326 and DeepSeek-V3.2-Exp score almost the same on the Noometry Index (43.8 vs 44.3), so choose on price, context window or the category you care about most.
Is Chatgpt 4o Latest 20250326 or DeepSeek-V3.2-Exp better for coding?
DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 versus 41.6 in the Noometry coding category.
How many benchmarks do Chatgpt 4o Latest 20250326 and DeepSeek-V3.2-Exp share?
19 benchmarks have published results for both models. Chatgpt 4o Latest 20250326 has 21 scored results on Noometry and DeepSeek-V3.2-Exp has 49.