Model decision surface
Compare AI models
Start with Ling 3.0 Flash and Qwen3 235B A22B, 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 vs Qwen3 235B A22B
Live dataset updated 9/10/2026, 11:40:10 AM UTC
Open 1200×630 evidence receipt| Field | Ling 3.0 Flash InclusionAI | Qwen3 235B A22B Qwen |
|---|---|---|
| ModelCap position | #78 | #81 |
| Index score | 50.9 | 50.3 |
| Evidence | Estimated4 reported rows against measured corpus ladders (49%); publisher-corpus-prior over 185 held-out anchors (51%); shrunk 6.1 toward the measured corpus | Measured2 public benchmark observations across 2 boards |
| Input / 1M | $0.021 | $0.455 |
| Output / 1M | $0.063 | $1.82 |
| Pricing status | fresh | fresh |
| Context | 262K | 131K |
| Providers | 2 | 1 |
| Weight access | Open weights | Open weights |
Decision facts
- Ling 3.0 Flash is #78; Qwen3 235B A22B is #81 on the same current language board.
- Index scores are 50.9 for Ling 3.0 Flash and 50.3 for Qwen3 235B A22B. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Ling 3.0 Flash is Estimated; Qwen3 235B A22B is Measured.
- Listed output price per 1M tokens is $0.06 for Ling 3.0 Flash and $1.82 for Qwen3 235B A22B. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.07 for Ling 3.0 Flash versus $1.82 for Qwen3 235B A22B. Ling 3.0 Flash costs 96.0% 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 262,144 tokens for Ling 3.0 Flash and 131,072 for Qwen3 235B A22B.
- ModelCap currently lists 2 providers for Ling 3.0 Flash and 1 for Qwen3 235B A22B.
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.