Model decision surface
Compare AI models
Start with Ling 3.0 Flash VL and Qwen3 235B A22B Instruct 2507, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.
Current public data
Ling 3.0 Flash VL vs Qwen3 235B A22B Instruct 2507
Live dataset updated 9/12/2026, 1:09:54 PM UTC
Open 1200×630 evidence receipt| Field | Ling 3.0 Flash VL InclusionAI | |
|---|---|---|
| ModelCap position | #56 | #58 |
| Index score | 58.1 | 57.6 |
| Evidence | Measured1 public benchmark observation across 1 board | Measured2 public benchmark observations across 2 boards |
| Input / 1M | $0.06 | $0.087 |
| Output / 1M | $0.18 | $0.35 |
| Pricing status | fresh | fresh |
| Context | 131K | 262K |
| Providers | 1 | 10 |
| Weight access | Open weights | Open weights |
Decision facts
- Ling 3.0 Flash VL is #56; Qwen3 235B A22B Instruct 2507 is #58 on the same current language board.
- Index scores are 58.1 for Ling 3.0 Flash VL and 57.6 for Qwen3 235B A22B Instruct 2507. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Both positions use Measured evidence.
- Listed output price per 1M tokens is $0.18 for Ling 3.0 Flash VL and $0.35 for Qwen3 235B A22B Instruct 2507. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.21 for Ling 3.0 Flash VL versus $0.35 for Qwen3 235B A22B Instruct 2507. Ling 3.0 Flash VL costs 40.0% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
- Published context is 131,072 tokens for Ling 3.0 Flash VL and 262,144 for Qwen3 235B A22B Instruct 2507.
- ModelCap currently lists 1 providers for Ling 3.0 Flash VL and 10 for Qwen3 235B A22B Instruct 2507.
These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.
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Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.