Ling 3.0 Flash VL vs Qwen2.5 7B Instruct

Ling 3.0 Flash VL and Qwen2.5 7B Instruct cost about the same per output token ($0.18 vs $0.20 per million). Updated October 23, 2026; no benchmark has tested both models yet.

Replace Ling 3.0 Flash VL Replace Qwen2.5 7B Instruct

Ling 3.0 Flash VLinclusionAI

Coding: No data
Overall: No data
Output $/M: $0.18

Qwen2.5 7B InstructQwen

Coding: No data
Overall: No data
Output $/M: $0.20

vs $0.18 vs $0.20 per 1M output tokens. Ling 3.0 Flash VL is 1.1x cheaper.

Ling 3.0 Flash VL or Qwen2.5 7B Instruct: which to pick

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

Pick Ling 3.0 Flash VL for output tokens 1.1x cheaper ($0.18 vs $0.20 per million) and a larger context window (131K against 33K tokens).

Model ALing 3.0 Flash VLinclusionAINot benchmarkedNo coding benchmarkNo cost per solved task Model BQwen2.5 7B InstructQwenNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. Ling 3.0 Flash VL has results on AA Coding Index, SciCode and AA Intelligence Index; Qwen2.5 7B Instruct on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI run). 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
Ling 3.0 Flash VL
Ling 3.0 Flash VL takes 131K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash VL
Ling 3.0 Flash VL $0.0001, Qwen2.5 7B Instruct $0.0002 per turn.
List prices

At a glance

Coding index: Ling 3.0 Flash VL not benchmarked, Qwen2.5 7B 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 3.0 Flash VL $0.18 against Qwen2.5 7B Instruct $0.20 per million output tokens, 1.1x apart.
Context window: Ling 3.0 Flash VL takes 131K tokens, Qwen2.5 7B Instruct 33K.

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 Index2 boards measured

Coding benchmarks for Ling 3.0 Flash VL and Qwen2.5 7B Instruct
Benchmark	Ling 3.0 Flash VL	Qwen2.5 7B Instruct	Leader
AA Coding Index	57.0	Not measured	Only Ling 3.0 Flash VL measured
SciCode	44.2%	Not measured	Only Ling 3.0 Flash VL measured
Neither model has a result on the other 41 boards here

IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured

Intelligence benchmarks for Ling 3.0 Flash VL and Qwen2.5 7B Instruct
Benchmark	Ling 3.0 Flash VL	Qwen2.5 7B Instruct	Leader
AA Intelligence Index	24.6	Not measured	Only Ling 3.0 Flash VL measured
Epoch Capabilities Index	Not measured	118.5	Only Qwen2.5 7B Instruct measured

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured

Agentic work benchmarks for Ling 3.0 Flash VL and Qwen2.5 7B Instruct
Benchmark	Ling 3.0 Flash VL	Qwen2.5 7B Instruct	Leader
AA Agentic Index	28.7	Not measured	Only Ling 3.0 Flash VL measured
BALROG	Not measured	7.8%	Only Qwen2.5 7B Instruct measured
Neither model has a result on the other 40 boards here

ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured

Reasoning benchmarks for Ling 3.0 Flash VL and Qwen2.5 7B Instruct
Benchmark	Ling 3.0 Flash VL	Qwen2.5 7B Instruct	Leader
GPQA Diamond (Artificial Analysis run)	86.2%	Not measured	Only Ling 3.0 Flash VL measured
Humanity's Last Exam (Artificial Analysis run)	22.0%	Not measured	Only Ling 3.0 Flash VL measured
GPQA Diamond (Epoch AI run)	Not measured	35.5%	Only Qwen2.5 7B Instruct measured
Neither model has a result on the other 20 boards here

MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured

Math benchmarks for Ling 3.0 Flash VL and Qwen2.5 7B Instruct
Benchmark	Ling 3.0 Flash VL	Qwen2.5 7B Instruct	Leader
OTIS Mock AIME	Not measured	2.5%	Only Qwen2.5 7B Instruct measured
Neither model has a result on the other 13 boards here

KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured

Knowledge benchmarks for Ling 3.0 Flash VL and Qwen2.5 7B Instruct
Benchmark	Ling 3.0 Flash VL	Qwen2.5 7B Instruct	Leader
MMLU	Not measured	72.9%	Only Qwen2.5 7B Instruct measured
Neither model has a result on the other 19 boards here

GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured

General benchmarks for Ling 3.0 Flash VL and Qwen2.5 7B Instruct
Benchmark	Ling 3.0 Flash VL	Qwen2.5 7B Instruct	Leader
Long context reasoning (AA-LCR)	78.3%	Not measured	Only Ling 3.0 Flash VL measured
DTBench	Not measured	47.7%	Only Qwen2.5 7B Instruct measured
LMCA	Not measured	6.4%	Only Qwen2.5 7B Instruct measured
Neither model has a result on the other 45 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$0.0001Fits in one request

Qwen2.5 7B Instruct$0.0002Fits in one request

Ling 3.0 Flash VL costs less

Repository review

50K input + 3K output tokens

Ling 3.0 Flash VL$0.0035Fits in one request

Qwen2.5 7B Instruct$0.0056Exceeds the context window

Ling 3.0 Flash VL costs less

Agent loop

200K input + 10K output tokens

Ling 3.0 Flash VL$0.014Exceeds the context window

Qwen2.5 7B Instruct$0.022Exceeds the context window

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.

Specifications of Ling 3.0 Flash VL and Qwen2.5 7B Instruct
Specification	inclusionAI Ling 3.0 Flash VL	Qwen2.5 7B Instruct
Maker	inclusionAI	Qwen
Weights	Open weights	Open weights
Released	September 10, 2026	October 16, 2024
Context window	131K	33K
Input $/Mtok	$0.06	$0.10
Output $/Mtok	$0.18	$0.20
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 Ling 3.0 Flash VL better than Qwen2.5 7B Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Ling 3.0 Flash VL for output tokens 1.1x cheaper ($0.18 vs $0.20 per million) and a larger context window (131K against 33K tokens).

Which is cheaper, Ling 3.0 Flash VL or Qwen2.5 7B Instruct?

Ling 3.0 Flash VL costs $0.06 per million input tokens and $0.18 per million output tokens; Qwen2.5 7B Instruct costs $0.10 and $0.20. Cost per solved task is known for neither of them.

Which has the bigger context window, Ling 3.0 Flash VL or Qwen2.5 7B Instruct?

Ling 3.0 Flash VL, with 131K tokens against 33K.

Has any benchmark tested both Ling 3.0 Flash VL and Qwen2.5 7B Instruct?

Ling 3.0 Flash VL or Qwen2.5 7B Instruct: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Long documents

Everyday cost

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

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