Mercury 2.5 vs Beam 1.0 501B A23B
Mercury 2.5 costs 7.3x less per output token than Beam 1.0 501B A23B ($0.15 vs $1.10 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 1.6
- Overall
- No data
- Output $/M
- $0.15
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.10
Mercury 2.5 or Beam 1.0 501B A23B: which to pick
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Beam 1.0 501B A23B has none, so the two cannot be ranked on coding.
Pick Beam 1.0 501B A23B for a larger context window (1.05M against 260K tokens).
No benchmark has tested both yet. Mercury 2.5 has results on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Code migration (Vals AI); 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
Only Mercury 2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Mercury 2.5 has a AA Intelligence Index result, 12.3.
Directional only
Web design
Design Arena: websites
No call
Only Beam 1.0 501B A23B has a Design Arena: websites result, 1250.
Directional only
Long documents
Listed context window
Beam 1.0 501B A23B
Beam 1.0 501B A23B takes 1.05M tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, Beam 1.0 501B A23B $0.0009 per turn.
List prices
At a glance
- Coding index
- Mercury 2.5 1.6 from 2 benchmarks, 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
- Mercury 2.5 $0.15 against Beam 1.0 501B A23B $1.10 per million output tokens, 7.3x apart.
- Context window
- Mercury 2.5 takes 260K 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 Index14 boards measured
| Benchmark | Mercury 2.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1437 | Only Beam 1.0 501B A23B measured |
| Terminal-Bench 4 (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 3.7% | Not measured | Only Mercury 2.5 measured |
| Code migration (Vals AI) | 4.5% | Not measured | Only Mercury 2.5 measured |
| IOI (Vals AI) | 2.4% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 34.5% | Not measured | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | 18.1% | Not measured | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | 45.5% | Not measured | Only Mercury 2.5 measured |
| SciCode | 38.5% | Not measured | Only Mercury 2.5 measured |
| ALE-Bench | 301.6 | Not measured | Only Mercury 2.5 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 25 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Mercury 2.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.3 | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Mercury 2.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Finance Agent (Vals AI) | 18.9% | Not measured | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | 2.5% | Not measured | Only Mercury 2.5 measured |
| Legal Research Bench (Vals AI) | 4.3% | Not measured | Only Mercury 2.5 measured |
| Excel Modeling Benchmark (Vals AI) | 8.8% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Mercury 2.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Humanity's Last Exam (Artificial Analysis run) | 11.8% | Not measured | Only Mercury 2.5 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 |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Mercury 2.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| ProofBench | 3.0% | Not measured | Only Mercury 2.5 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 index6 boards measured
| Benchmark | Mercury 2.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.1% | Not measured | Only Mercury 2.5 measured |
| MedCode (Vals AI) | 31.3% | Not measured | Only Mercury 2.5 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 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Mercury 2.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1250 | Only Beam 1.0 501B A23B measured |
| Design Arena: game dev | Not measured | 1224 | 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 index15 boards measured
| Benchmark | Mercury 2.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 45.3% | Not measured | Only Mercury 2.5 measured |
| MedScribe (Vals AI) | 55.1% | Not measured | Only Mercury 2.5 measured |
| Long context reasoning (AA-LCR) | 71.7% | Not measured | Only Mercury 2.5 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 31 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
Mercury 2.5 costs less
Repository review
50K input + 3K output tokens
Mercury 2.5 costs less
Agent loop
200K input + 10K output tokens
Mercury 2.5 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 | Inception Mercury 2.5 | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | Inception | Reflection |
| Weights | No public weights listed | Open weights |
| Released | September 8, 2026 | October 16, 2026 |
| Context window | 260K | 1.05M |
| Input $/Mtok | $0.04 | $0.35 |
| Output $/Mtok | $0.15 | $1.10 |
| Coding index | 1.6 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 better than Beam 1.0 501B A23B for coding?
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Beam 1.0 501B A23B has none, so the two cannot be ranked on coding. Pick Beam 1.0 501B A23B for a larger context window (1.05M against 260K tokens).
Which is cheaper, Mercury 2.5 or Beam 1.0 501B A23B?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 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, Mercury 2.5 or Beam 1.0 501B A23B?
Beam 1.0 501B A23B, with 1.05M tokens against 260K.
Has any benchmark tested both Mercury 2.5 and Beam 1.0 501B A23B?
No benchmark has tested both yet. Mercury 2.5 has results on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Code migration (Vals AI); 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 22, 2026.