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Head-to-head comparison

Ling-3.0-flash vs Qwen3 235B A22B Instruct 2507

Ling-3.0-flash (InclusionAI) and Qwen3 235B A22B Instruct 2507 (Qwen) compared on the ModelCap Index, API price, context window, provider availability, weight access and every public benchmark board they share. Figures are the same ones shown on the live rankings; nothing here is a hidden score.

Snapshot as of 3 September 2026

As of 3 September 2026, Ling-3.0-flash holds the stronger ModelCap Index position (#49 vs #50); and Ling-3.0-flash is 5.6× cheaper per output token ($0.063/1M vs $0.35/1M).

Which should you choose?

Choose Ling-3.0-flash if…

  • you want the stronger overall ModelCap Index position — #49 against #50 (51.7 vs 50.2 points).
  • API cost matters — $0.063/1M output tokens against $0.35/1M, about 5.6× cheaper.
  • your workload is prompt-heavy — input tokens cost $0.021/1M against $0.087/1M.
  • AA Intelligence Index is your yardstick — 37.8 against 18.4.
  • AA Humanity's Last Exam is your yardstick — 23.7% against 11.1%.
  • you want the more recently listed model — Ling-3.0-flash was listed 23 July 2026, Qwen3 235B A22B Instruct 2507 21 July 2025.

Choose Qwen3 235B A22B Instruct 2507 if…

  • you want provider choice — 10 listed API providers against 2.

Ling-3.0-flash vs Qwen3 235B A22B Instruct 2507: specs, pricing and context

Specification comparison of Ling-3.0-flash and Qwen3 235B A22B Instruct 2507
FieldLing-3.0-flashInclusionAIQwen3 235B A22B Instruct 2507Qwen
ModelCap Index position#49#50
Index score51.750.2
EvidenceMeasuredMeasured
Input price / 1M tokens$0.021$0.087
Output price / 1M tokens$0.063$0.35
Context window262K tokens262K tokens
Max output tokens33K236K
API providers listed210
Weight accessOpen weightsOpen weights
Input modalitiesTextText
First listed23 July 202621 July 2025
PublisherInclusionAIQwen

Evidence: 1 public benchmark observation across 1 board · 4 public benchmark observations across 4 boards. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.

Benchmark scores: Ling-3.0-flash vs Qwen3 235B A22B Instruct 2507

Public benchmark boards where Ling-3.0-flash or Qwen3 235B A22B Instruct 2507 has a published result
BoardLing-3.0-flashQwen3 235B A22B Instruct 2507Leads
Arena codingArena (LMArena)—14721468–1477Only one result
ARC-AGI-2ARC Prize Foundation—1.3%Only one result
BFCL V4UC Berkeley (Gorilla)—52.2PromptOnly one result
AA Intelligence IndexArtificial Analysis37.8intelligence-index18.4intelligence-indexLing-3.0-flash
AA Terminal-Bench 2.1Artificial Analysis55.4%terminal-bench-2.1—Only one result
AA τ²-Bench TelecomArtificial Analysis—33.3%tau2-bench-telecomOnly one result
AA Humanity's Last ExamArtificial Analysis23.7%humanitys-last-exam11.1%humanitys-last-examLing-3.0-flash

Scores are the sources' own published figures for each model's best evaluated configuration; ModelCap never re-runs a benchmark.

Want a different pairing? Open the interactive comparison tool to swap either model for any current ranked language model.

Ling-3.0-flash vs Qwen3 235B A22B Instruct 2507: common questions

Is Ling-3.0-flash better than Qwen3 235B A22B Instruct 2507?

Ling-3.0-flash ranks higher on the ModelCap Index as of 3 September 2026: #49 against #50. That is a capability ranking built from public benchmark evidence with published uncertainty; whether it is "better" for you also depends on price, context and where you can run it.

Is Ling-3.0-flash cheaper than Qwen3 235B A22B Instruct 2507?

Ling-3.0-flash is cheaper on output tokens: $0.063/1M against $0.35/1M. Input tokens are $0.021/1M for Ling-3.0-flash and $0.087/1M for Qwen3 235B A22B Instruct 2507. Prices are the lowest listed API offer ModelCap observed, in USD per million tokens.

Which has the bigger context window, Ling-3.0-flash or Qwen3 235B A22B Instruct 2507?

Both publish a 262K-token context window.

Which is better for coding, Ling-3.0-flash or Qwen3 235B A22B Instruct 2507?

The two models do not share a coding benchmark board on ModelCap yet, so no head-to-head coding score is published; the ModelCap Index position is the closest overall signal.

Are Ling-3.0-flash and Qwen3 235B A22B Instruct 2507 open-weight models?

Ling-3.0-flash: Open weights. Qwen3 235B A22B Instruct 2507: Open weights. Open weights mean the checkpoint can be downloaded and self-hosted under its licence; API-only models are available solely through hosted endpoints.

Where can I run Ling-3.0-flash and Qwen3 235B A22B Instruct 2507?

ModelCap currently lists 2 API providers for Ling-3.0-flash and 10 for Qwen3 235B A22B Instruct 2507, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.

How current is this Ling-3.0-flash vs Qwen3 235B A22B Instruct 2507 comparison?

Every figure comes from the sealed ModelCap dataset published 3 September 2026; the page re-renders within a minute of each data refresh, and the ModelCap Index positions are the same ones shown on the live rankings.

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