GPT-5 Pro vs Ling 3.0 Flash
Ling 3.0 Flash costs 987.7x less per output token than GPT-5 Pro ($0.1215 vs $120.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $120.00
- Coding
- 29.6
- Overall
- No data
- Output $/M
- $0.1215
GPT-5 Pro or Ling 3.0 Flash: which to pick
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; GPT-5 Pro has none, so the two cannot be ranked on coding.
Pick GPT-5 Pro for a larger context window (400K against 262K tokens).
No benchmark has tested both yet. GPT-5 Pro has results on WeirdML, Epoch Capabilities Index and ARC-AGI; Ling 3.0 Flash on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI). 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 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
GPT-5 Pro
GPT-5 Pro takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
GPT-5 Pro $0.075, 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
- GPT-5 Pro not benchmarked, Ling 3.0 Flash 29.6 from 2 benchmarks.
- 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
- GPT-5 Pro $120.00 against Ling 3.0 Flash $0.1215 per million output tokens, 987.7x apart.
- Context window
- GPT-5 Pro takes 400K tokens, Ling 3.0 Flash 262K.
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 Index9 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 50.6 | Only Ling 3.0 Flash measured |
| LiveCodeBench (Vals AI) | Not measured | 84.0% | Only Ling 3.0 Flash measured |
| 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 |
| SciCode | Not measured | 42.0% | Only Ling 3.0 Flash measured |
| WeirdML | 60.4% | Not measured | Only GPT-5 Pro measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 20.1 | Only Ling 3.0 Flash measured |
| Epoch Capabilities Index | 150.6 | Not measured | Only GPT-5 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-5 Pro | 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 |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.8% | Only Ling 3.0 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 85.5% | Only Ling 3.0 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 23.7% | Only Ling 3.0 Flash measured |
| ARC-AGI | 70.2% | Not measured | Only GPT-5 Pro measured |
| ARC-AGI-2 | 18.3% | Not measured | Only GPT-5 Pro measured |
| SimpleBench | 61.6% | Not measured | Only GPT-5 Pro measured |
| Chess puzzles | 48.0% | Not measured | Only GPT-5 Pro measured |
| Kagi LLM Benchmark | 76.8% | Not measured | Only GPT-5 Pro measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | 55.8% | Not measured | Only GPT-5 Pro measured |
| FrontierMath, tier 4 | 19.5% | Not measured | Only GPT-5 Pro measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-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 |
| 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 |
| Neither model has a result on the other 13 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-5 Pro | 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 |
| Neither model has a result on the other 43 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 | OpenAI GPT-5 Pro | inclusionAI Ling 3.0 Flash |
|---|---|---|
| Maker | OpenAI | inclusionAI |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2025 | July 23, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $15.00 | $0.0405 |
| Output $/Mtok | $120.00 | $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 GPT-5 Pro better than Ling 3.0 Flash for coding?
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; GPT-5 Pro has none, so the two cannot be ranked on coding. Pick GPT-5 Pro for a larger context window (400K against 262K tokens).
Which is cheaper, GPT-5 Pro or Ling 3.0 Flash?
GPT-5 Pro costs $15.00 per million input tokens and $120.00 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, GPT-5 Pro or Ling 3.0 Flash?
GPT-5 Pro, with 400K tokens against 262K.
Has any benchmark tested both GPT-5 Pro and Ling 3.0 Flash?
No benchmark has tested both yet. GPT-5 Pro has results on WeirdML, Epoch Capabilities Index and ARC-AGI; Ling 3.0 Flash on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI). Compare them on price and context instead. Data as of October 22, 2026.