Gemini 2.5 Pro Preview 06-05 vs Ling 3.0 Flash
Ling 3.0 Flash costs 82.3x less per output token than Gemini 2.5 Pro Preview 06-05 ($0.1215 vs $10.00 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
Gemini 2.5 Pro Preview 06-05 or Ling 3.0 Flash: which to pick
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding.
Pick Gemini 2.5 Pro Preview 06-05 for a larger context window (1.05M against 262K tokens).
- Shared results
- 3
- Gemini 2.5 Pro Preview 06-05 only
- 12
- Ling 3.0 Flash only
- 21
- Like-for-like categories
- 2 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
No call
Only Ling 3.0 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Ling 3.0 Flash has a AA Intelligence Index result, 20.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash has a AA Agentic Index result, 19.3.
Directional only
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
Long documents
Listed context window
Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Gemini 2.5 Pro Preview 06-05 $0.0063, Ling 3.0 Flash $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Ling 3.0 Flash has the number, $0.05.
Directional only
At a glance
- Coding index
- Gemini 2.5 Pro Preview 06-05 not benchmarked, Ling 3.0 Flash 29.6 from 2 benchmarks.
- Widest category
- Coding, 4.8 points apart on average over 1 shared benchmark.
- Widest single gap
- LiveCodeBench (Vals AI): Gemini 2.5 Pro Preview 06-05 79.2% against Ling 3.0 Flash 84.0%, 4.8 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro Preview 06-05 $10.00 against Ling 3.0 Flash $0.1215 per million output tokens, 82.3x apart.
- Context window
- Gemini 2.5 Pro Preview 06-05 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 Preview 06-05 | Bars | Ling 3.0 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| All shared boards | 0 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Aider polyglot | 83.1% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| AA Coding Index | Not measured | 50.6 | Only Ling 3.0 Flash measured |
| LiveCodeBench (Vals AI) | 79.2% | 84.0% | Ling 3.0 Flash |
| SWE-bench Verified (Vals AI) | Not measured | 65.2% | Only Ling 3.0 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 2.9% | Only Ling 3.0 Flash measured |
| 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) | 77.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| SciCode | Not measured | 42.0% | Only Ling 3.0 Flash measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| SciCode | 7.7% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 20.1 | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 19.3 | Only Ling 3.0 Flash measured |
| 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 |
| METR time horizons | 55.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Remote Labor Index | 0.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| DeepResearch Bench | 42.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.8% | Only Ling 3.0 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 83.6% | 85.5% | Ling 3.0 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 19.9% | 23.7% | Ling 3.0 Flash |
| GPQA Diamond (Epoch AI run) | 84.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| SimpleBench | 62.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| VPCT | 46.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 16 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | 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 |
| CorpFin (Vals AI) | Not measured | 61.9% | Only Ling 3.0 Flash measured |
| TaxEval (Vals AI) | Not measured | 70.7% | Only Ling 3.0 Flash measured |
| MedCode (Vals AI) | Not measured | 32.3% | Only Ling 3.0 Flash measured |
| MMLU Pro (Artificial Analysis run) | 85.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 50.7% | Only Ling 3.0 Flash measured |
| MedScribe (Vals AI) | Not measured | 80.9% | Only Ling 3.0 Flash measured |
| Long context reasoning (AA-LCR) | Not measured | 73.0% | Only Ling 3.0 Flash measured |
| Fiction.LiveBench | 91.7% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | 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 Preview 06-05 | inclusionAI Ling 3.0 Flash |
|---|---|---|
| Maker | inclusionAI | |
| Weights | No public weights listed | Open weights |
| Released | June 5, 2025 | July 23, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $1.25 | $0.0405 |
| Output $/Mtok | $10.00 | $0.1215 |
| Coding index | Not benchmarked | 29.6 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $0.05 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro Preview 06-05 better than Ling 3.0 Flash for coding?
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Pro Preview 06-05 for a larger context window (1.05M against 262K tokens).
Which is cheaper, Gemini 2.5 Pro Preview 06-05 or Ling 3.0 Flash?
Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; Ling 3.0 Flash costs $0.0405 and $0.1215. Cost per solved task is known for Ling 3.0 Flash only.
Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or Ling 3.0 Flash?
Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 262K.
How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs Ling 3.0 Flash comparison based on?
3 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro Preview 06-05's coding index rests on 0 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.