GPT-4o-mini vs Beam 1.0 501B A23B
GPT-4o-mini costs 1.8x less per output token than Beam 1.0 501B A23B ($0.60 vs $1.10 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.60
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.10
GPT-4o-mini or Beam 1.0 501B A23B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o-mini for output tokens 1.8x cheaper ($0.60 vs $1.10 per million).
No benchmark has tested both yet. GPT-4o-mini has results on AA Coding Index, LiveCodeBench (Vals AI) and LiveCodeBench (Artificial Analysis run); Beam 1.0 501B A23B on LMArena WebDev, LMArena Text: coding and LMArena Text: software and IT. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-4o-mini has a AA Intelligence Index result, 6.7.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4o-mini has a GPQA Diamond result, 44.2%.
Directional only
Math
AIME
No call
Only GPT-4o-mini has a AIME result, 11.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o-mini has a MMLU Pro result, 62.7%.
Directional only
Web design
Design Arena: websites
No call
Only Beam 1.0 501B A23B has a Design Arena: websites result, 1253.
Directional only
Long documents
Listed context window
Beam 1.0 501B A23B
Beam 1.0 501B A23B takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o-mini
GPT-4o-mini $0.0004, Beam 1.0 501B A23B $0.0009 per turn.
List prices
At a glance
- Coding index
- GPT-4o-mini not benchmarked, Beam 1.0 501B A23B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-4o-mini $0.60 against Beam 1.0 501B A23B $1.10 per million output tokens, 1.8x apart.
- Context window
- GPT-4o-mini takes 128K tokens, Beam 1.0 501B A23B 1.05M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards measured
| Benchmark | GPT-4o-mini | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1437 | Only Beam 1.0 501B A23B measured |
| AA Coding Index | 11.4 | Not measured | Only GPT-4o-mini measured |
| LiveCodeBench (Vals AI) | 26.4% | Not measured | Only GPT-4o-mini measured |
| LiveCodeBench (Artificial Analysis run) | 23.4% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: coding | Not measured | 1473 | Only Beam 1.0 501B A23B measured |
| LMArena Text: software and IT | Not measured | 1461 | Only Beam 1.0 501B A23B measured |
| LMArena WebDev: React | Not measured | 1443 | Only Beam 1.0 501B A23B measured |
| LMArena WebDev: HTML | Not measured | 1436 | Only Beam 1.0 501B A23B measured |
| SciCode | 1.5% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-4o-mini | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | Not measured | Only GPT-4o-mini measured |
| Epoch Capabilities Index | 126.5 | Not measured | Only GPT-4o-mini measured |
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | GPT-4o-mini | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| GPQA Diamond | 44.2% | Not measured | Only GPT-4o-mini measured |
| MMMU Pro (Vals AI) | 56.6% | Not measured | Only GPT-4o-mini measured |
| GPQA Diamond (Artificial Analysis run) | 42.6% | Not measured | Only GPT-4o-mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | Not measured | Only GPT-4o-mini measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: hard prompts | Not measured | 1442 | Only Beam 1.0 501B A23B measured |
| LMArena Text: expert | Not measured | 1447 | Only Beam 1.0 501B A23B measured |
| LMArena Text: hard prompts in English | Not measured | 1451 | Only Beam 1.0 501B A23B measured |
| Kagi LLM Benchmark | 28.8% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | GPT-4o-mini | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AIME | 11.5% | Not measured | Only GPT-4o-mini measured |
| MATH 500 (Vals AI) | 72.6% | Not measured | Only GPT-4o-mini measured |
| MGSM (Vals AI) | 86.2% | Not measured | Only GPT-4o-mini measured |
| AA Math Index | 14.7 | Not measured | Only GPT-4o-mini measured |
| AIME 2025 (Artificial Analysis run) | 14.7% | Not measured | Only GPT-4o-mini measured |
| GSM8K | 91.3% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: math | Not measured | 1459 | Only Beam 1.0 501B A23B measured |
| LMArena Text: mathematical work | Not measured | 1475 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards measured
| Benchmark | GPT-4o-mini | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| MMLU Pro | 62.7% | Not measured | Only GPT-4o-mini measured |
| CorpFin (Vals AI) | 45.5% | Not measured | Only GPT-4o-mini measured |
| TaxEval (Vals AI) | 60.5% | Not measured | Only GPT-4o-mini measured |
| MortgageTax (Vals AI) | 54.5% | Not measured | Only GPT-4o-mini measured |
| MedQA (Vals AI) | 72.4% | Not measured | Only GPT-4o-mini measured |
| MMLU Pro (Artificial Analysis run) | 64.8% | Not measured | Only GPT-4o-mini measured |
| MMLU | 81.8% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: science | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| LMArena Text: medicine and healthcare | Not measured | 1376 | Only Beam 1.0 501B A23B measured |
| LMArena Text: legal and government | Not measured | 1433 | Only Beam 1.0 501B A23B measured |
| LMArena Text: business and finance | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-4o-mini | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1253 | Only Beam 1.0 501B A23B measured |
| Design Arena: game dev | Not measured | 1233 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 7 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index16 boards measured
| Benchmark | GPT-4o-mini | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| IFBench | 31.0% | Not measured | Only GPT-4o-mini measured |
| DTBench | 54.4% | Not measured | Only GPT-4o-mini measured |
| LMCA | 10.4% | Not measured | Only GPT-4o-mini measured |
| PIQA | 88.7% | Not measured | Only GPT-4o-mini measured |
| LMArena Text | Not measured | 1425 | Only Beam 1.0 501B A23B measured |
| LMArena Text: instruction following | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| LMArena Text: creative writing | Not measured | 1390 | Only Beam 1.0 501B A23B measured |
| LMArena Text: English | Not measured | 1436 | Only Beam 1.0 501B A23B measured |
| LMArena Text: non-English | Not measured | 1413 | Only Beam 1.0 501B A23B measured |
| LMArena Text: Chinese | Not measured | 1424 | Only Beam 1.0 501B A23B measured |
| LMArena Text: French | Not measured | 1461 | Only Beam 1.0 501B A23B measured |
| LMArena Text: Russian | Not measured | 1412 | Only Beam 1.0 501B A23B measured |
| LMArena Text: multi-turn | Not measured | 1414 | Only Beam 1.0 501B A23B measured |
| LMArena Text: longer queries | Not measured | 1429 | Only Beam 1.0 501B A23B measured |
| LMArena Text: writing and language | Not measured | 1400 | Only Beam 1.0 501B A23B measured |
| LMArena Text: entertainment and media | Not measured | 1399 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 30 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
GPT-4o-mini costs less
Repository review
50K input + 3K output tokens
GPT-4o-mini costs less
Agent loop
200K input + 10K output tokens
GPT-4o-mini costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-4o-mini | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | OpenAI | Reflection |
| Weights | No public weights listed | Open weights |
| Released | July 18, 2024 | October 16, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $0.15 | $0.35 |
| Output $/Mtok | $0.60 | $1.10 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o-mini better than Beam 1.0 501B A23B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o-mini for output tokens 1.8x cheaper ($0.60 vs $1.10 per million).
Which is cheaper, GPT-4o-mini or Beam 1.0 501B A23B?
GPT-4o-mini costs $0.15 per million input tokens and $0.60 per million output tokens; Beam 1.0 501B A23B costs $0.35 and $1.10. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o-mini or Beam 1.0 501B A23B?
Beam 1.0 501B A23B, with 1.05M tokens against 128K.
Has any benchmark tested both GPT-4o-mini and Beam 1.0 501B A23B?
No benchmark has tested both yet. GPT-4o-mini has results on AA Coding Index, LiveCodeBench (Vals AI) and LiveCodeBench (Artificial Analysis run); Beam 1.0 501B A23B on LMArena WebDev, LMArena Text: coding and LMArena Text: software and IT. Compare them on price and context instead. Data as of October 21, 2026.