Gemini 2.5 Pro vs Ling 3.0 Flash
Ling 3.0 Flash leads Gemini 2.5 Pro on coding, 29.6 to 19.1 on the Vibe Coding Index, and Ling 3.0 Flash costs 82.3x less per output token ($0.1215 vs $10.00 per million). Updated October 22, 2026; 12 benchmarks have a result for both.
Gemini 2.5 Pro or Ling 3.0 Flash: which to pick
Pick Ling 3.0 Flash for coding: it scores 29.6 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro, though on 2 benchmarks against 3.
Pick Gemini 2.5 Pro for a larger context window (1.05M against 262K tokens) and work measured by SciCode or MedCode (Vals AI), where it leads.
- Shared results
- 12
- Gemini 2.5 Pro only
- 78
- Ling 3.0 Flash only
- 12
- Like-for-like categories
- 6 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
Ling 3.0 Flash
Ling 3.0 Flash scores 29.6 against 19.1.
3 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Ling 3.0 Flash
Ling 3.0 Flash leads, 20.1 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
Ling 3.0 Flash
Ling 3.0 Flash leads, 19.3 against 1.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Ling 3.0 Flash has a GPQA Diamond result, 84.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Ling 3.0 Flash has a MMLU Pro result, 82.0%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 2.5 Pro has a Design Arena: websites result, 1167.
Directional only
Long documents
Listed context window
Gemini 2.5 Pro
Gemini 2.5 Pro takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Gemini 2.5 Pro $0.0063, Ling 3.0 Flash $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Ling 3.0 Flash
Gemini 2.5 Pro $0.64, Ling 3.0 Flash $0.05.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Pro 19.1 from 3 benchmarks, Ling 3.0 Flash 29.6 from 2 benchmarks.
- Widest category
- Agentic work, 17.7 points apart on average over 1 shared benchmark.
- Widest single gap
- MedCode (Vals AI): Gemini 2.5 Pro 50.6% against Ling 3.0 Flash 32.3%, 18.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against Ling 3.0 Flash $0.1215 per million output tokens, 82.3x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, Ling 3.0 Flash 262K.
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 2.5 Pro | Bars | Ling 3.0 Flash | Ties |
|---|---|---|---|---|
| Coding | 1 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Knowledge | 1 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 2 | 10 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index13
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev | 1226 | Not measured | Only Gemini 2.5 Pro measured |
| AA Coding Index | 33.3 | 50.6 | Ling 3.0 Flash |
| LiveCodeBench (Vals AI) | Not measured | 84.0% | Only Ling 3.0 Flash measured |
| SWE-bench Verified (Vals AI) | 54.4% | 65.2% | Ling 3.0 Flash |
| Vibe Code Bench (Vals AI) | 0.4% | 2.9% | Ling 3.0 Flash |
| Code migration (Vals AI) | Not measured | 0.0% | Only Ling 3.0 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 50.2% | Only Ling 3.0 Flash measured |
| SkillsBench (Vals AI) | Not measured | 27.9% | Only Ling 3.0 Flash measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 42.0% | Gemini 2.5 Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: coding | 1452 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: software and IT | 1459 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev: HTML | 1235 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev: from an image | 1285 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 20.1 | Ling 3.0 Flash |
| Epoch Capabilities Index | 145.1 | Not measured | Only Gemini 2.5 Pro measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | 19.3 | Ling 3.0 Flash |
| Finance Agent (Vals AI) | Not measured | 30.3% | Only Ling 3.0 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 0.0% | Only Ling 3.0 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 25.0% | Only Ling 3.0 Flash measured |
| τ²-Bench Telecom | 54.1% | Not measured | Only Gemini 2.5 Pro measured |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | $574 | Not measured | Only Gemini 2.5 Pro measured |
| BrowseComp-Plus | 29.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.8% | Only Ling 3.0 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | 85.5% | Ling 3.0 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 23.7% | Ling 3.0 Flash |
| GPQA Diamond (Epoch AI run) | 85.3% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI | 41.0% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: hard prompts | 1455 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: expert | 1452 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: hard prompts in English | 1453 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: diagrams | 1274 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: homework | 1281 | Not measured | Only Gemini 2.5 Pro measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 10 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierMath, tiers 1 to 3 | 24.6% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierMath, tier 4 | 0.0% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: math | 1450 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: mathematical work | 1454 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.0% | Only Ling 3.0 Flash measured |
| LegalBench (Vals AI) | Not measured | 79.7% | Only Ling 3.0 Flash measured |
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | 61.9% | Ling 3.0 Flash |
| TaxEval (Vals AI) | Not measured | 70.7% | Only Ling 3.0 Flash measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedCode (Vals AI) | 50.6% | 32.3% | Gemini 2.5 Pro |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: science | 1480 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: medicine and healthcare | 1476 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: legal and government | 1480 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: business and finance | 1439 | Not measured | Only Gemini 2.5 Pro measured |
| FACTS Benchmark Suite | 61.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: UI components | 1137 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: game dev | 1111 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: data viz | 1222 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: 3D | 1080 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: all code categories | 1152 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 50.7% | Only Ling 3.0 Flash measured |
| SAGE (Vals AI) | 41.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedScribe (Vals AI) | 73.5% | 80.9% | Ling 3.0 Flash |
| IFBench | 48.7% | Not measured | Only Gemini 2.5 Pro measured |
| Long context reasoning (AA-LCR) | 69.0% | 73.0% | Ling 3.0 Flash |
| DTBench | 82.4% | Not measured | Only Gemini 2.5 Pro measured |
| LMCA | 34.8% | Not measured | Only Gemini 2.5 Pro measured |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text | 1458 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: instruction following | 1437 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: creative writing | 1454 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision | 1263 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: English | 1458 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: non-English | 1452 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Chinese | 1507 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: German | 1487 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Japanese | 1461 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Korean | 1434 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: French | 1473 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Spanish | 1474 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Russian | 1461 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Polish | 1479 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: multi-turn | 1453 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: longer queries | 1449 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: writing and language | 1454 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: entertainment and media | 1441 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: English | 1261 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: Chinese | 1300 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: reading text | 1270 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: humor | 1262 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: creative writing | 1265 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | Ling 3.0 Flash | 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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash 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 2.5 Pro | inclusionAI Ling 3.0 Flash |
|---|---|---|
| Maker | inclusionAI | |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | July 23, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $1.25 | $0.0405 |
| Output $/Mtok | $10.00 | $0.1215 |
| Coding index | 19.1 | 29.6 |
| Independent measurements behind it | 3 | 2 |
| Cost per solved task | $0.64 | $0.05 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than Ling 3.0 Flash for coding?
Pick Ling 3.0 Flash for coding: it scores 29.6 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro, though on 2 benchmarks against 3. Pick Gemini 2.5 Pro for a larger context window (1.05M against 262K tokens) and work measured by SciCode or MedCode (Vals AI), where it leads.
Which is cheaper, Gemini 2.5 Pro or Ling 3.0 Flash?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Ling 3.0 Flash costs $0.0405 and $0.1215. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and Ling 3.0 Flash $0.05.
Which has the bigger context window, Gemini 2.5 Pro or Ling 3.0 Flash?
Gemini 2.5 Pro, with 1.05M tokens against 262K.
How many benchmarks is the Gemini 2.5 Pro vs Ling 3.0 Flash comparison based on?
12 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 independent benchmarks and Ling 3.0 Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.