Model comparison
Gemini 4 Argon vs GPT-5-Codex
Gemini 4 Argon is the stronger model overall, scoring 56.5 to 37.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
GoogleSummary
- The widest gap is in coding, where Gemini 4 Argon leads 62.0 to 42.4.
Side by side
| Gemini 4 Argon | GPT-5-Codex | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 56.5 | 37.9 |
| Released | 2026-09-30 | 2025-09-15 |
| Weights | Proprietary | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $1.25 |
| Output $ / M tokens | — | $10 |
| Results tracked | 21 | 3 |
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Category by category
Coding Gemini 4 Argon leads
Gemini 4 Argon: 62.0 (#9), GPT-5-Codex: 42.4 (#103)
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| LMArena WebDev | 1678 | — |
| FrontierSWE | 55% | — |
| SciCode | 61.8% | — |
| WeirdML | — | 54.5% |
| LMArena Coding | 1550 | — |
Agentic & Tool Use Gemini 4 Argon leads
Gemini 4 Argon: 49.2 (#8), GPT-5-Codex: 31.0 (#72)
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| Terminal-Bench | — | 44.3% |
| APEX-Agents | 82.2% | — |
| Vending-Bench 2 | 13,718 | — |
Reasoning Gemini 4 Argon leads
Gemini 4 Argon: 44.2 (#47), GPT-5-Codex: 30.9 (#83)
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| Kagi LLM Benchmark | — | 70.3% |
| CritPt | 27.1% | — |
| LMArena Hard Prompts | 1548 | — |
Math Not comparable
Gemini 4 Argon: 73.9 (#17), GPT-5-Codex: —
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| ProofBench | 99% | — |
| LMArena Math | 1536 | — |
Knowledge Not comparable
Gemini 4 Argon: 43.9 (#89), GPT-5-Codex: —
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| LMArena Expert | 1553 | — |
Multimodal Not comparable
Gemini 4 Argon: 46.5 (#14), GPT-5-Codex: —
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| Blueprint-Bench 2 | 54.4% | — |
Multilingual Not comparable
Gemini 4 Argon: 60.3 (#1), GPT-5-Codex: —
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| LMArena Non-English | 1523 | — |
| LMArena Chinese | 1610 | — |
| LMArena Russian | 1537 | — |
| LMArena Spanish | 1497 | — |
Instruction Following Not comparable
Gemini 4 Argon: 80.1 (#2), GPT-5-Codex: —
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| LMArena Instruction Following | 1538 | — |
Long Context Not comparable
Gemini 4 Argon: 47.6 (#15), GPT-5-Codex: —
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| LMArena Longer Query | 1549 | — |
Writing & Preference Not comparable
Gemini 4 Argon: 71.4 (#19), GPT-5-Codex: —
| Benchmark | Gemini 4 Argon | GPT-5-Codex |
|---|---|---|
| LMArena Text | 1534 | — |
| LMArena Creative Writing | 1531 | — |
| LMArena Multi-Turn | 1557 | — |
Frequently asked questions
Is Gemini 4 Argon better than GPT-5-Codex?
Gemini 4 Argon is the stronger model overall, scoring 56.5 to 37.9 on the Noometry Index.
Is Gemini 4 Argon or GPT-5-Codex better for coding?
Gemini 4 Argon scores higher on coding benchmarks: 62.0 versus 42.4 in the Noometry coding category.
How many benchmarks do Gemini 4 Argon and GPT-5-Codex share?
0 benchmarks have published results for both models. Gemini 4 Argon has 21 scored results on Noometry and GPT-5-Codex has 3.