Model comparison
GPT-5.3 Codex vs Yi-1.5-34B
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 30.6 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in coding, where GPT-5.3 Codex leads 48.6 to 32.4.
- Yi-1.5-34B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Codex | Yi-1.5-34B | |
|---|---|---|
| Provider | OpenAI | 01.AI |
| Noometry Index | 45.8 | 30.6 |
| Released | 2026-02-05 | 2024-05-13 |
| Weights | Proprietary | Open |
| Context window | 400K | — |
| Max output | 128K | — |
| Input $ / M tokens | $1.75 | — |
| Output $ / M tokens | $14 | — |
| Results tracked | 8 | 21 |
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Category by category
Coding GPT-5.3 Codex leads
GPT-5.3 Codex: 48.6 (#56), Yi-1.5-34B: 32.4 (#272)
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| SWE-bench Verified | 74.8% | — |
| LMArena WebDev | 1409 | — |
| WeirdML | 79.3% | — |
| BigCodeBench Instruct | — | 33.9% |
| LMArena Coding | — | 1169 |
| BigCodeBench Complete | — | 43.8% |
| ALE-Bench | 1,655 | — |
Agentic & Tool Use Not comparable
GPT-5.3 Codex: 48.0 (#9), Yi-1.5-34B: —
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| Terminal-Bench | 78.4% | — |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Yi-1.5-34B: 22.5 (#191)
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| LMArena Hard Prompts | — | 1160 |
| Epoch Capabilities Index | 156.77 | — |
Math Not comparable
GPT-5.3 Codex: —, Yi-1.5-34B: 27.5 (#249)
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| LMArena Math | — | 1182 |
| MATH Level 5 | — | 25.5% |
Knowledge Not comparable
GPT-5.3 Codex: —, Yi-1.5-34B: 14.8 (#295)
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| GPQA Diamond | — | 32% |
| LMArena Expert | — | 1144 |
Multilingual Not comparable
GPT-5.3 Codex: —, Yi-1.5-34B: 32.3 (#256)
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| LMArena Non-English | — | 1121 |
| LMArena Chinese | — | 1213 |
| LMArena French | — | 1156 |
| LMArena German | — | 1111 |
| LMArena Japanese | — | 1021 |
| LMArena Korean | — | 1005 |
| LMArena Russian | — | 1091 |
| LMArena Spanish | — | 1121 |
Instruction Following Not comparable
GPT-5.3 Codex: —, Yi-1.5-34B: 59.2 (#257)
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| LMArena Instruction Following | — | 1139 |
Long Context Not comparable
GPT-5.3 Codex: —, Yi-1.5-34B: 34.6 (#248)
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| LMArena Longer Query | — | 1143 |
Writing & Preference Not comparable
GPT-5.3 Codex: —, Yi-1.5-34B: 37.4 (#257)
| Benchmark | GPT-5.3 Codex | Yi-1.5-34B |
|---|---|---|
| LMArena Text | — | 1173 |
| LMArena Creative Writing | — | 1135 |
| LMArena Multi-Turn | — | 1153 |
Frequently asked questions
Is GPT-5.3 Codex better than Yi-1.5-34B?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 30.6 on the Noometry Index.
Is GPT-5.3 Codex or Yi-1.5-34B better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 32.4 in the Noometry coding category.
How many benchmarks do GPT-5.3 Codex and Yi-1.5-34B share?
0 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Yi-1.5-34B has 21.