GPT-5.1-Codex-Max vs Beam 1.0 501B A23B
Beam 1.0 501B A23B costs 9.1x less per output token than GPT-5.1-Codex-Max ($1.10 vs $10.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.10
GPT-5.1-Codex-Max or Beam 1.0 501B A23B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. GPT-5.1-Codex-Max has results on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench; 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
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 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Beam 1.0 501B A23B
GPT-5.1-Codex-Max $0.0063, Beam 1.0 501B A23B $0.0009 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Max 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-5.1-Codex-Max $10.00 against Beam 1.0 501B A23B $1.10 per million output tokens, 9.1x apart.
- Context window
- GPT-5.1-Codex-Max takes 400K 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-5.1-Codex-Max | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1437 | Only Beam 1.0 501B A23B measured |
| LiveCodeBench (Vals AI) | 83.6% | Not measured | Only GPT-5.1-Codex-Max measured |
| Vibe Code Bench (Vals AI) | 22.2% | Not measured | Only GPT-5.1-Codex-Max measured |
| Terminal-Bench | 60.4% | Not measured | Only GPT-5.1-Codex-Max measured |
| ALE-Bench | 1228.3 | Not measured | Only GPT-5.1-Codex-Max 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 |
| Neither model has a result on the other 30 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.1-Codex-Max | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| METR time horizons | 70.8% | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-5.1-Codex-Max | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| 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 |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-5.1-Codex-Max | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only GPT-5.1-Codex-Max 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 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-5.1-Codex-Max | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| 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 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5.1-Codex-Max | 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 index12 boards measured
| Benchmark | GPT-5.1-Codex-Max | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| 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 34 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
Beam 1.0 501B A23B costs less
Repository review
50K input + 3K output tokens
Beam 1.0 501B A23B costs less
Agent loop
200K input + 10K output tokens
Beam 1.0 501B A23B 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-5.1-Codex-Max | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | OpenAI | Reflection |
| Weights | No public weights listed | Open weights |
| Released | December 4, 2025 | October 16, 2026 |
| Context window | 400K | 1.05M |
| Input $/Mtok | $1.25 | $0.35 |
| Output $/Mtok | $10.00 | $1.10 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Max better than Beam 1.0 501B A23B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-5.1-Codex-Max or Beam 1.0 501B A23B?
GPT-5.1-Codex-Max costs $1.25 per million input tokens and $10.00 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-5.1-Codex-Max or Beam 1.0 501B A23B?
Beam 1.0 501B A23B, with 1.05M tokens against 400K.
Has any benchmark tested both GPT-5.1-Codex-Max and Beam 1.0 501B A23B?
No benchmark has tested both yet. GPT-5.1-Codex-Max has results on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench; 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.