Model comparison
GPT-4.1 mini vs GPT-5-Codex
GPT-5-Codex is the stronger model overall, scoring 37.3 to 33.5 on the Noometry Index. GPT-4.1 mini costs 4.9× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Summary
- They share 2 benchmarks with published results for both. GPT-4.1 mini scores higher in 1 category and GPT-5-Codex in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5-Codex leads 30.0 to 10.9.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 48.6% for GPT-4.1 mini and 70.3% for GPT-5-Codex.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-4.1 mini | GPT-5-Codex | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 33.5 | 37.3 |
| Released | 2025-04-14 | 2025-09-15 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 33K | 128K |
| Input $ / M tokens | $0.40 | $1.25 |
| Output $ / M tokens | $1.60 | $10 |
| Results tracked | 47 | 3 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5-Codex leads
GPT-4.1 mini: 30.4 (#286), GPT-5-Codex: 41.9 (#100)
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| WeirdML | 37.6% | 54.5% |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| SciCode | 40.4% | — |
| BigCodeBench Instruct | 48.9% | — |
| LMArena Coding | 1367 | — |
| CadEval | 16% | — |
Agentic & Tool Use GPT-4.1 mini leads
GPT-4.1 mini: 33.0 (#52), GPT-5-Codex: 30.8 (#66)
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| Terminal-Bench | — | 44.3% |
| Berkeley Function Calling Leaderboard | 50.5% | — |
Reasoning GPT-5-Codex leads
GPT-4.1 mini: 10.9 (#335), GPT-5-Codex: 30.0 (#80)
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| Kagi LLM Benchmark | 48.6% | 70.3% |
| ARC-AGI-2 | 0% | — |
| ARC-AGI-1 | 3.5% | — |
| CritPt | 0% | — |
| Chess Puzzles | 7% | — |
| LMArena Hard Prompts | 1349 | — |
| Mystery Game Puzzles | 7% | — |
| DTBench | 68.8% | — |
| LMCA | 21.1% | — |
| Epoch Capabilities Index | 135.01 | — |
Math Not comparable
GPT-4.1 mini: 23.1 (#264), GPT-5-Codex: —
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | — |
| OTIS Mock AIME 2024-2025 | 44.7% | — |
| Omni-MATH | 49.1% | — |
| LMArena Math | 1343 | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge Not comparable
GPT-4.1 mini: 34.7 (#183), GPT-5-Codex: —
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| GPQA Diamond | 65.8% | — |
| SimpleQA Verified | 12.7% | — |
| MMLU-Pro | 78.3% | — |
| GPQA (HELM) | 61.4% | — |
| LMArena Expert | 1338 | — |
Multimodal Not comparable
GPT-4.1 mini: 35.2 (#77), GPT-5-Codex: —
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| LMArena Vision | 1181 | — |
Multilingual Not comparable
GPT-4.1 mini: 45.9 (#161), GPT-5-Codex: —
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| LMArena Non-English | 1318 | — |
| LMArena Chinese | 1329 | — |
| LMArena French | 1357 | — |
| LMArena German | 1349 | — |
| LMArena Japanese | 1291 | — |
| LMArena Korean | 1298 | — |
| LMArena Russian | 1324 | — |
| LMArena Spanish | 1319 | — |
Instruction Following Not comparable
GPT-4.1 mini: 73.9 (#113), GPT-5-Codex: —
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| IFEval | 90.4% | — |
| LMArena Instruction Following | 1332 | — |
Long Context Not comparable
GPT-4.1 mini: 31.8 (#270), GPT-5-Codex: —
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| Fiction.LiveBench | 44.4% | — |
| LMArena Longer Query | 1344 | — |
Writing & Preference Not comparable
GPT-4.1 mini: 48.8 (#193), GPT-5-Codex: —
| Benchmark | GPT-4.1 mini | GPT-5-Codex |
|---|---|---|
| LMArena Text | 1341 | — |
| LMArena Creative Writing | 1300 | — |
| EQ-Bench Creative Writing | 1147 | — |
| WildBench | 83.8% | — |
| LMArena Multi-Turn | 1354 | — |
Frequently asked questions
Is GPT-4.1 mini better than GPT-5-Codex?
GPT-5-Codex is the stronger model overall, scoring 37.3 to 33.5 on the Noometry Index. GPT-4.1 mini costs 4.9× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 mini or GPT-5-Codex?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GPT-5-Codex lists at $1.25 and $10.
Is GPT-4.1 mini or GPT-5-Codex better for coding?
GPT-5-Codex scores higher on coding benchmarks: 41.9 versus 30.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 400K.
How many benchmarks do GPT-4.1 mini and GPT-5-Codex share?
2 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and GPT-5-Codex has 3.