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Ling 3.1 Flash vs Qwen2.5 VL 72B Instruct

Ling 3.1 Flash costs 4.4x less per output token than Qwen2.5 VL 72B Instruct ($0.225 vs $1.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace Ling 3.1 Flash Replace Qwen2.5 VL 72B Instruct
Ling 3.1 FlashinclusionAI
Coding
No data
Overall
No data
Output $/M
$0.225
Qwen2.5 VL 72B InstructQwen
Coding
No data
Overall
No data
Output $/M
$1.00
vs $0.225 vs $1.00 per 1M output tokens. Ling 3.1 Flash is 4.4x cheaper.

Ling 3.1 Flash or Qwen2.5 VL 72B Instruct: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Ling 3.1 Flash for output tokens 4.4x cheaper ($0.225 vs $1.00 per million) and a larger context window (262K against 128K tokens).

Model ALing 3.1 FlashinclusionAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen2.5 VL 72B InstructQwenNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. Ling 3.1 Flash has results on SciCode, AA Intelligence Index and Humanity's Last Exam (Artificial Analysis run); Qwen2.5 VL 72B Instruct on OSWorld, Kagi LLM Benchmark and GeoBench. 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.

At a glance

Coding index
Ling 3.1 Flash not benchmarked, Qwen2.5 VL 72B Instruct 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
Ling 3.1 Flash $0.225 against Qwen2.5 VL 72B Instruct $1.00 per million output tokens, 4.4x apart.
Context window
Ling 3.1 Flash takes 262K tokens, Qwen2.5 VL 72B Instruct 128K.

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 Index1 board measured
Coding benchmarks for Ling 3.1 Flash and Qwen2.5 VL 72B Instruct
BenchmarkLing 3.1 FlashQwen2.5 VL 72B InstructLeader
SciCode54.1%Not measuredOnly Ling 3.1 Flash measured
Neither model has a result on the other 42 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for Ling 3.1 Flash and Qwen2.5 VL 72B Instruct
BenchmarkLing 3.1 FlashQwen2.5 VL 72B InstructLeader
AA Intelligence Index41.1Not measuredOnly Ling 3.1 Flash measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Agentic work benchmarks for Ling 3.1 Flash and Qwen2.5 VL 72B Instruct
BenchmarkLing 3.1 FlashQwen2.5 VL 72B InstructLeader
OSWorldNot measured5.0%Only Qwen2.5 VL 72B Instruct measured
Neither model has a result on the other 41 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Reasoning benchmarks for Ling 3.1 Flash and Qwen2.5 VL 72B Instruct
BenchmarkLing 3.1 FlashQwen2.5 VL 72B InstructLeader
Humanity's Last Exam (Artificial Analysis run)39.4%Not measuredOnly Ling 3.1 Flash measured
Kagi LLM BenchmarkNot measured36.0%Only Qwen2.5 VL 72B Instruct measured
Neither model has a result on the other 21 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Knowledge benchmarks for Ling 3.1 Flash and Qwen2.5 VL 72B Instruct
BenchmarkLing 3.1 FlashQwen2.5 VL 72B InstructLeader
GeoBenchNot measured62.0%Only Qwen2.5 VL 72B Instruct measured
Neither model has a result on the other 19 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
General benchmarks for Ling 3.1 Flash and Qwen2.5 VL 72B Instruct
BenchmarkLing 3.1 FlashQwen2.5 VL 72B InstructLeader
Long context reasoning (AA-LCR)83.0%Not measuredOnly Ling 3.1 Flash measured
LMArena VisionNot measured1107Only Qwen2.5 VL 72B Instruct measured
LMArena Vision: EnglishNot measured1115Only Qwen2.5 VL 72B Instruct measured
LMArena Vision: ChineseNot measured1107Only Qwen2.5 VL 72B Instruct measured
Neither model has a result on the other 44 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 3.1 Flash$0.0002Fits in one request
Qwen2.5 VL 72B Instruct$0.0013Fits in one request

Ling 3.1 Flash costs less

Repository review

50K input + 3K output tokens

Ling 3.1 Flash$0.0044Fits in one request
Qwen2.5 VL 72B Instruct$0.043Fits in one request

Ling 3.1 Flash costs less

Agent loop

200K input + 10K output tokens

Ling 3.1 Flash$0.017Fits in one request
Qwen2.5 VL 72B Instruct$0.170Exceeds the context window

Ling 3.1 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.

Specifications of Ling 3.1 Flash and Qwen2.5 VL 72B Instruct
SpecificationinclusionAI Ling 3.1 FlashQwen2.5 VL 72B Instruct
MakerinclusionAIQwen
WeightsNo public weights listedOpen weights
ReleasedOctober 2, 2026February 1, 2025
Context window262K128K
Input $/Mtok$0.075$0.80
Output $/Mtok$0.225$1.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Ling 3.1 Flash better than Qwen2.5 VL 72B Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Ling 3.1 Flash for output tokens 4.4x cheaper ($0.225 vs $1.00 per million) and a larger context window (262K against 128K tokens).

Which is cheaper, Ling 3.1 Flash or Qwen2.5 VL 72B Instruct?

Ling 3.1 Flash costs $0.075 per million input tokens and $0.225 per million output tokens; Qwen2.5 VL 72B Instruct costs $0.80 and $1.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Ling 3.1 Flash or Qwen2.5 VL 72B Instruct?

Ling 3.1 Flash, with 262K tokens against 128K.

Has any benchmark tested both Ling 3.1 Flash and Qwen2.5 VL 72B Instruct?

No benchmark has tested both yet. Ling 3.1 Flash has results on SciCode, AA Intelligence Index and Humanity's Last Exam (Artificial Analysis run); Qwen2.5 VL 72B Instruct on OSWorld, Kagi LLM Benchmark and GeoBench. Compare them on price and context instead. Data as of October 22, 2026.

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