Gemini 3.7 Flash vs Beam 1.0 501B A23B
Updated October 21, 2026. 28 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 28 shared
Decision reading
Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 33.8 for Beam 1.0 501B A23B.
Pick Beam 1.0 501B A23B when output tokens cost 3.8x less.
Model AGemini 3.7 FlashGoogle69.9/1002 independent benchmarks$1.78 per solved taskModel BBeam 1.0 501B A23BReflection33.8/1001 independent benchmarkNo cost per solved task
- Shared results
- 28
- Gemini 3.7 Flash only
- 84
- Beam 1.0 501B A23B only
- 0
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Gemini 3.7 Flash
Gemini 3.7 Flash scores 69.9 against 33.8.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Gemini 3.7 Flash has a AA Intelligence Index result, 39.6.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.7 Flash has a GPQA Diamond result, 93.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.7 Flash has a MMLU Pro result, 90.1%.
Directional only
Web design
Design Arena: websites
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 1304 against 1253.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Beam 1.0 501B A23B
Gemini 3.7 Flash $0.0026, Beam 1.0 501B A23B $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.7 Flash has the number, $1.78.
Directional only
At a glance
- Coding index
- Gemini 3.7 Flash 69.9 from 2 benchmarks, Beam 1.0 501B A23B 33.8 from 1 benchmark.
- Widest category
- Coding, 16.6 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena WebDev: HTML: Gemini 3.7 Flash 1593 against Beam 1.0 501B A23B 1436, 26.2 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.7 Flash $3.75 against Beam 1.0 501B A23B $1.00 per million output tokens, 3.8x apart.
- Context window
- Both take 1.05M tokens.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Gemini 3.7 Flash | Bars | Beam 1.0 501B A23B | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 2 | 0 | ||
| General | 12 | 0 | ||
| All shared boards | 28 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench coding | 80.5% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena WebDev | 1591 | 1437 | Gemini 3.7 Flash |
| AA Coding Index | 71.5 | Not measured | Only Gemini 3.7 Flash measured |
| LiveCodeBench (Vals AI) | 88.7% | Not measured | Only Gemini 3.7 Flash measured |
| SWE-bench Verified (Vals AI) | 80.8% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench 4 (Vals AI) | 12.1% | Not measured | Only Gemini 3.7 Flash measured |
| Vibe Code Bench (Vals AI) | 70.4% | Not measured | Only Gemini 3.7 Flash measured |
| Code migration (Vals AI) | 34.8% | Not measured | Only Gemini 3.7 Flash measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.7 Flash measured |
| IOI (Vals AI) | 67.8% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 77.5% | Not measured | Only Gemini 3.7 Flash measured |
| SkillsBench (Vals AI) | 65.9% | Not measured | Only Gemini 3.7 Flash measured |
| CyberBench (Vals AI) | 43.8% | Not measured | Only Gemini 3.7 Flash measured |
| SciCode | 59.8% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierCode | 43.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierSWE | 20.3% | Not measured | Only Gemini 3.7 Flash measured |
| ALE-Bench | 904.3 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: coding | 1499 | 1473 | Gemini 3.7 Flash |
| LMArena Text: software and IT | 1498 | 1461 | Gemini 3.7 Flash |
| LMArena WebDev: React | 1587 | 1443 | Gemini 3.7 Flash |
| LMArena WebDev: HTML | 1593 | 1436 | Gemini 3.7 Flash |
| LMArena WebDev: from an image | 1599 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 39.6 | Not measured | Only Gemini 3.7 Flash measured |
| Epoch Capabilities Index | 158.0 | Not measured | Only Gemini 3.7 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1224 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building full-stack apps | 1208 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building mobile apps | 1230 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | 1247 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Godot games | 1264 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building games | 1235 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: spreadsheets | 1028 | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench research | 76.5% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench browser | 56.0% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench long agentic | 28.3% | Not measured | Only Gemini 3.7 Flash measured |
| SREBench (Vals AI) | 4.6% | Not measured | Only Gemini 3.7 Flash measured |
| Finance Agent (Vals AI) | 59.0% | Not measured | Only Gemini 3.7 Flash measured |
| Tax Agent Bench (Vals AI) | 22.8% | Not measured | Only Gemini 3.7 Flash measured |
| Legal Research Bench (Vals AI) | 34.6% | Not measured | Only Gemini 3.7 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 71.3% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench-Science (Vals AI) | 7.1% | Not measured | Only Gemini 3.7 Flash measured |
| APEX-Agents | 67.8% | Not measured | Only Gemini 3.7 Flash measured |
| Remote Labor Index | 5.0% | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| GPQA Diamond | 93.9% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench reasoning | 87.8% | Not measured | Only Gemini 3.7 Flash measured |
| MMMU Pro (Vals AI) | 89.0% | Not measured | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 94.5% | Not measured | Only Gemini 3.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 47.9% | Not measured | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Epoch AI run) | 94.8% | Not measured | Only Gemini 3.7 Flash measured |
| ARC-AGI | 95.5% | Not measured | Only Gemini 3.7 Flash measured |
| ARC-AGI-2 | 84.6% | Not measured | Only Gemini 3.7 Flash measured |
| Chess puzzles | 66.0% | Not measured | Only Gemini 3.7 Flash measured |
| Mystery game puzzles | 37.0% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts | 1495 | 1442 | Gemini 3.7 Flash |
| LMArena Text: expert | 1512 | 1447 | Gemini 3.7 Flash |
| LMArena Text: hard prompts in English | 1487 | 1451 | Gemini 3.7 Flash |
| LMArena Vision: diagrams | 1329 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: homework | 1320 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 97.2% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | 71.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierMath, tier 4 | 36.6% | Not measured | Only Gemini 3.7 Flash measured |
| ProofBench | 58.0% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: math | 1511 | 1459 | Gemini 3.7 Flash |
| LMArena Text: mathematical work | 1502 | 1475 | Gemini 3.7 Flash |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| MMLU Pro | 90.1% | Not measured | Only Gemini 3.7 Flash measured |
| LegalBench (Vals AI) | 87.3% | Not measured | Only Gemini 3.7 Flash measured |
| TaxEval (Vals AI) | 74.7% | Not measured | Only Gemini 3.7 Flash measured |
| MortgageTax (Vals AI) | 66.7% | Not measured | Only Gemini 3.7 Flash measured |
| MedCode (Vals AI) | 53.4% | Not measured | Only Gemini 3.7 Flash measured |
| SimpleQA Verified | 69.2% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: science | 1511 | 1430 | Gemini 3.7 Flash |
| LMArena Text: medicine and healthcare | 1494 | 1376 | Gemini 3.7 Flash |
| LMArena Text: legal and government | 1496 | 1433 | Gemini 3.7 Flash |
| LMArena Text: business and finance | 1479 | 1430 | Gemini 3.7 Flash |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | 1304 | 1253 | Gemini 3.7 Flash |
| Design Arena: UI components | 1299 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: game dev | 1318 | 1222 | Gemini 3.7 Flash |
| Design Arena: data viz | 1315 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: 3D | 1308 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: all code categories | 1308 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: SVG | 1283 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: ASCII art | 1276 | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench design | 73.2% | Not measured | Only Gemini 3.7 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench data analysis | 68.0% | Not measured | Only Gemini 3.7 Flash measured |
| SAGE (Vals AI) | 49.2% | Not measured | Only Gemini 3.7 Flash measured |
| MedScribe (Vals AI) | 83.9% | Not measured | Only Gemini 3.7 Flash measured |
| Long context reasoning (AA-LCR) | 83.0% | Not measured | Only Gemini 3.7 Flash measured |
| DTBench | 96.8% | Not measured | Only Gemini 3.7 Flash measured |
| LMCA | 50.4% | Not measured | Only Gemini 3.7 Flash measured |
| Furniture assembly | 26.7% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text | 1489 | 1425 | Gemini 3.7 Flash |
| LMArena Text: instruction following | 1484 | 1430 | Gemini 3.7 Flash |
| LMArena Text: creative writing | 1488 | 1390 | Gemini 3.7 Flash |
| LMArena Vision | 1314 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: English | 1483 | 1436 | Gemini 3.7 Flash |
| LMArena Text: non-English | 1487 | 1413 | Gemini 3.7 Flash |
| LMArena Text: Chinese | 1552 | 1424 | Gemini 3.7 Flash |
| LMArena Text: German | 1506 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Japanese | 1511 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Korean | 1481 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: French | 1500 | 1461 | Gemini 3.7 Flash |
| LMArena Text: Spanish | 1495 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Russian | 1515 | 1412 | Gemini 3.7 Flash |
| LMArena Text: Polish | 1503 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: multi-turn | 1485 | 1414 | Gemini 3.7 Flash |
| LMArena Text: longer queries | 1492 | 1429 | Gemini 3.7 Flash |
| LMArena Text: writing and language | 1491 | 1400 | Gemini 3.7 Flash |
| LMArena Text: entertainment and media | 1477 | 1399 | Gemini 3.7 Flash |
| LMArena Vision: English | 1309 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: Chinese | 1394 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: reading text | 1322 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: humor | 1299 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: creative writing | 1312 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.7 Flash | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Neither model has a result on 5 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
Gemini 3.7 Flash$0.0026Fits in one request
Beam 1.0 501B A23B$0.0008Fits in one request
Beam 1.0 501B A23B costs less
Repository review
50K input + 3K output tokens
Gemini 3.7 Flash$0.049Fits in one request
Beam 1.0 501B A23B$0.018Fits in one request
Beam 1.0 501B A23B costs less
Agent loop
200K input + 10K output tokens
Gemini 3.7 Flash$0.188Fits in one request
Beam 1.0 501B A23B$0.070Fits in one request
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 | Google Gemini 3.7 Flash | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | Reflection | |
| Weights | No public weights listed | Open weights |
| Released | August 13, 2026 | October 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.75 | $0.30 |
| Output $/Mtok | $3.75 | $1.00 |
| Coding index | 69.9 | 33.8 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $1.78 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.7 Flash better than Beam 1.0 501B A23B for coding?
Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 33.8 for Beam 1.0 501B A23B. Pick Beam 1.0 501B A23B when output tokens cost 3.8x less.
Which is cheaper, Gemini 3.7 Flash or Beam 1.0 501B A23B?
Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Beam 1.0 501B A23B costs $0.30 and $1.00. Cost per solved task is known for Gemini 3.7 Flash only.
Which has the bigger context window, Gemini 3.7 Flash or Beam 1.0 501B A23B?
Neither: both take 1.05M tokens.
How many benchmarks is the Gemini 3.7 Flash vs Beam 1.0 501B A23B comparison based on?
28 benchmarks have a result for both models as of October 21, 2026. Gemini 3.7 Flash's coding index rests on 2 independent benchmarks and Beam 1.0 501B A23B's on 1. Where only one model has a result, the page says so instead of naming a winner.