Gemini 3.5 Flash vs Weaver (alpha)
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Gemini 3.5 FlashGoogle
- Coding
- 39.8
- Overall
- 33.6
- Output $/M
- $9.00
M Weaver (alpha)Mancer
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.75
vs $9.00 vs $0.75 per 1M output tokens. Weaver (alpha) is 12.0x cheaper.
Decision reading
Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; Weaver (alpha) has none, so the two cannot be ranked on coding.
Weaver (alpha) has the edge where output tokens cost 12.0x less.
Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BWeaver (alpha)MancerNot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 0
- Gemini 3.5 Flash only
- 110
- Weaver (alpha) only
- 0
- Like-for-like categories
- 0 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, six public coding benchmarks
No call
Only Gemini 3.5 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Gemini 3.5 Flash has a AA Intelligence Index result, 33.6.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.5 Flash has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.5 Flash has a MMLU Pro result, 89.5%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 3.5 Flash has a Design Arena: websites result, 1268.
Directional only
Long documents
Listed context window
Gemini 3.5 Flash
Gemini 3.5 Flash takes 1.05M tokens against 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Weaver (alpha)
Gemini 3.5 Flash $0.0060, Weaver (alpha) $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.5 Flash has the number, $1.21.
Directional only
At a glance
- Coding index
- Gemini 3.5 Flash 39.8 from 4 benchmarks, Weaver (alpha) not benchmarked.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- Gemini 3.5 Flash $9.00 against Weaver (alpha) $0.75 per million output tokens, 12.0x apart.
- Context window
- Gemini 3.5 Flash takes 1.05M tokens, Weaver (alpha) 8K.
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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index18 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | Leader |
|---|---|---|---|
| LMArena WebDev | 1499 | Not measured | Only Gemini 3.5 Flash measured |
| LiveCodeBench (Vals AI) | 87.6% | Not measured | Only Gemini 3.5 Flash measured |
| SWE-bench Verified (Vals AI) | 78.8% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 4 (Vals AI) | 6.1% | Not measured | Only Gemini 3.5 Flash measured |
| Vibe Code Bench (Vals AI) | 48.7% | Not measured | Only Gemini 3.5 Flash measured |
| Code migration (Vals AI) | 26.8% | Not measured | Only Gemini 3.5 Flash measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.2% | Not measured | Only Gemini 3.5 Flash measured |
| SkillsBench (Vals AI) | 52.7% | Not measured | Only Gemini 3.5 Flash measured |
| SciCode | 53.9% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | 46.2% | Not measured | Only Gemini 3.5 Flash measured |
| WeirdML | 62.6% | Not measured | Only Gemini 3.5 Flash measured |
| ALE-Bench | 911.0 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: coding | 1493 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: software and IT | 1494 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena WebDev: React | 1495 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena WebDev: HTML | 1522 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena WebDev: from an image | 1504 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | Leader |
|---|---|---|---|
| AA Intelligence Index | 33.6 | Not measured | Only Gemini 3.5 Flash measured |
| Epoch Capabilities Index | 154.9 | Not measured | Only Gemini 3.5 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1202 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building full-stack apps | 1197 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building mobile apps | 1175 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Android apps | 1190 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Godot games | 1098 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building games | 1180 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: HTML slides | 1142 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: PowerPoint slides | 1179 | Not measured | Only Gemini 3.5 Flash measured |
| Finance Agent (Vals AI) | 57.9% | Not measured | Only Gemini 3.5 Flash measured |
| Tax Agent Bench (Vals AI) | 21.6% | Not measured | Only Gemini 3.5 Flash measured |
| Legal Research Bench (Vals AI) | 30.8% | Not measured | Only Gemini 3.5 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 63.5% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only Gemini 3.5 Flash measured |
| τ²-Bench Telecom | 95.6% | Not measured | Only Gemini 3.5 Flash measured |
| APEX-Agents | 27.5% | Not measured | Only Gemini 3.5 Flash measured |
| Vending-Bench 2 | $5,396 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | Leader |
|---|---|---|---|
| GPQA Diamond | 92.7% | Not measured | Only Gemini 3.5 Flash measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only Gemini 3.5 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 92.2% | Not measured | Only Gemini 3.5 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 42.7% | Not measured | Only Gemini 3.5 Flash measured |
| GPQA Diamond (Epoch AI run) | 92.8% | Not measured | Only Gemini 3.5 Flash measured |
| ARC-AGI | 92.5% | Not measured | Only Gemini 3.5 Flash measured |
| ARC-AGI-2 | 72.1% | Not measured | Only Gemini 3.5 Flash measured |
| SimpleBench | 76.7% | Not measured | Only Gemini 3.5 Flash measured |
| Chess puzzles | 45.0% | Not measured | Only Gemini 3.5 Flash measured |
| Mystery game puzzles | 32.0% | Not measured | Only Gemini 3.5 Flash measured |
| EBR-bench | 4.8% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: hard prompts | 1488 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: expert | 1495 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: hard prompts in English | 1483 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: diagrams | 1323 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: homework | 1330 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 5 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | Leader |
|---|---|---|---|
| OTIS Mock AIME | 95.6% | Not measured | Only Gemini 3.5 Flash measured |
| FrontierMath, tiers 1 to 3 | 62.8% | Not measured | Only Gemini 3.5 Flash measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only Gemini 3.5 Flash measured |
| ProofBench | 31.0% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: math | 1504 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: mathematical work | 1495 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | Leader |
|---|---|---|---|
| MMLU Pro | 89.5% | Not measured | Only Gemini 3.5 Flash measured |
| LegalBench (Vals AI) | 83.6% | Not measured | Only Gemini 3.5 Flash measured |
| CorpFin (Vals AI) | 64.7% | Not measured | Only Gemini 3.5 Flash measured |
| TaxEval (Vals AI) | 74.4% | Not measured | Only Gemini 3.5 Flash measured |
| MortgageTax (Vals AI) | 68.1% | Not measured | Only Gemini 3.5 Flash measured |
| MedCode (Vals AI) | 55.8% | Not measured | Only Gemini 3.5 Flash measured |
| SimpleQA Verified | 66.2% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: science | 1495 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: medicine and healthcare | 1483 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: legal and government | 1488 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: business and finance | 1467 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: UI components | 1273 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: game dev | 1263 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: data viz | 1236 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: 3D | 1244 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: all code categories | 1266 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: SVG | 1254 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: ASCII art | 1254 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index33 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 59.5% | Not measured | Only Gemini 3.5 Flash measured |
| SAGE (Vals AI) | 49.9% | Not measured | Only Gemini 3.5 Flash measured |
| MedScribe (Vals AI) | 76.6% | Not measured | Only Gemini 3.5 Flash measured |
| Vals Multimodal Index | 62.9% | Not measured | Only Gemini 3.5 Flash measured |
| IFBench | 76.3% | Not measured | Only Gemini 3.5 Flash measured |
| Long context reasoning (AA-LCR) | 74.3% | Not measured | Only Gemini 3.5 Flash measured |
| DTBench | 94.7% | Not measured | Only Gemini 3.5 Flash measured |
| LMCA | 47.1% | Not measured | Only Gemini 3.5 Flash measured |
| Surface Evolver Bench | 58.1% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text | 1482 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: instruction following | 1467 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: creative writing | 1470 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision | 1308 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: English | 1481 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: non-English | 1475 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Chinese | 1527 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: German | 1494 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Japanese | 1486 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Korean | 1448 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: French | 1490 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Spanish | 1480 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Russian | 1493 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Polish | 1516 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: multi-turn | 1481 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: longer queries | 1483 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: writing and language | 1478 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: entertainment and media | 1459 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: English | 1305 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: Chinese | 1377 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: reading text | 1317 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: humor | 1321 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Document | 1463 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash | Weaver (alpha) | 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 3.5 Flash$0.0060Fits in one request
Weaver (alpha)$0.0008Fits in one request
Weaver (alpha) costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash$0.102Fits in one request
Weaver (alpha)$0.022Exceeds the context window
Weaver (alpha) costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 Flash$0.390Fits in one request
Weaver (alpha)$0.087Exceeds the context window
Weaver (alpha) 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 3.5 Flash | Mancer Weaver (alpha) |
|---|---|---|
| Maker | Mancer | |
| Weights | No public weights listed | No public weights listed |
| Released | May 19, 2026 | August 2, 2023 |
| Context window | 1.05M | 8K |
| Input $/Mtok | $1.50 | $0.40 |
| Output $/Mtok | $9.00 | $0.75 |
| Coding index | 39.8 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $1.21 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash better than Weaver (alpha) for coding?
Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; Weaver (alpha) has none, so the two cannot be ranked on coding. Weaver (alpha) has the edge where output tokens cost 12.0x less.
Which is cheaper, Gemini 3.5 Flash or Weaver (alpha)?
Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; Weaver (alpha) costs $0.40 and $0.75. Cost per solved task is known for Gemini 3.5 Flash only.
Which has the bigger context window, Gemini 3.5 Flash or Weaver (alpha)?
Gemini 3.5 Flash, with 1.05M tokens against 8K.
How many benchmarks is the Gemini 3.5 Flash vs Weaver (alpha) comparison based on?
0 benchmarks have a result for both models as of October 21, 2026. Gemini 3.5 Flash's coding index rests on 4 independent benchmarks and Weaver (alpha)'s on 0. Where only one model has a result, the page says so instead of naming a winner.