GPT-5 Pro vs Ling 3.0 Flash VL
Ling 3.0 Flash VL costs 666.7x less per output token than GPT-5 Pro ($0.18 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
- No data
- Overall
- No data
- Output $/M
- $0.18
GPT-5 Pro or Ling 3.0 Flash VL: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5 Pro for a larger context window (400K against 131K tokens).
No benchmark has tested both yet. GPT-5 Pro has results on WeirdML, Epoch Capabilities Index and ARC-AGI; Ling 3.0 Flash VL on AA Coding Index, SciCode and AA Intelligence Index. 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Ling 3.0 Flash VL has a AA Intelligence Index result, 24.6.
Directional only
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash VL has a AA Agentic Index result, 28.7.
Directional only
Long documents
Listed context window
GPT-5 Pro
GPT-5 Pro takes 400K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash VL
GPT-5 Pro $0.075, Ling 3.0 Flash VL $0.0001 per turn.
List prices
At a glance
- Coding index
- GPT-5 Pro not benchmarked, Ling 3.0 Flash VL not benchmarked.
- 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 VL $0.18 per million output tokens, 666.7x apart.
- Context window
- GPT-5 Pro takes 400K tokens, Ling 3.0 Flash VL 131K.
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 Index3 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 57.0 | Only Ling 3.0 Flash VL measured |
| SciCode | Not measured | 44.2% | Only Ling 3.0 Flash VL measured |
| WeirdML | 60.4% | Not measured | Only GPT-5 Pro measured |
| Neither model has a result on the other 40 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 24.6 | Only Ling 3.0 Flash VL measured |
| Epoch Capabilities Index | 150.6 | Not measured | Only GPT-5 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 28.7 | Only Ling 3.0 Flash VL measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 86.2% | Only Ling 3.0 Flash VL measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 22.0% | Only Ling 3.0 Flash VL 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 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash VL | 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 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| PRBench Finance | 51.1% | Not measured | Only GPT-5 Pro measured |
| PRBench Legal | 49.9% | Not measured | Only GPT-5 Pro measured |
| Neither model has a result on the other 18 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5 Pro | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 78.3% | Only Ling 3.0 Flash VL measured |
| Neither model has a result on the other 47 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 VL costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash VL costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash VL 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 VL |
|---|---|---|
| Maker | OpenAI | inclusionAI |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2025 | September 10, 2026 |
| Context window | 400K | 131K |
| Input $/Mtok | $15.00 | $0.06 |
| Output $/Mtok | $120.00 | $0.18 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Pro better than Ling 3.0 Flash VL for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5 Pro for a larger context window (400K against 131K tokens).
Which is cheaper, GPT-5 Pro or Ling 3.0 Flash VL?
GPT-5 Pro costs $15.00 per million input tokens and $120.00 per million output tokens; Ling 3.0 Flash VL costs $0.06 and $0.18. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5 Pro or Ling 3.0 Flash VL?
GPT-5 Pro, with 400K tokens against 131K.
Has any benchmark tested both GPT-5 Pro and Ling 3.0 Flash VL?
No benchmark has tested both yet. GPT-5 Pro has results on WeirdML, Epoch Capabilities Index and ARC-AGI; Ling 3.0 Flash VL on AA Coding Index, SciCode and AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.