Qwen2.5 VL 72B Instruct vs Qwen3.8 2.4T A95B

Qwen2.5 VL 72B Instruct costs 6.0x less per output token than Qwen3.8 2.4T A95B ($1.00 vs $6.00 per million). Updated October 23, 2026; no benchmark has tested both models yet.

Replace Qwen2.5 VL 72B Instruct Replace Qwen3.8 2.4T A95B

Qwen2.5 VL 72B InstructQwen

Coding: No data
Overall: No data
Output $/M: $1.00

Qwen3.8 2.4T A95BQwen

Coding: No data
Overall: No data
Output $/M: $6.00

vs $1.00 vs $6.00 per 1M output tokens. Qwen2.5 VL 72B Instruct is 6.0x cheaper.

Qwen2.5 VL 72B Instruct or Qwen3.8 2.4T A95B: which to pick

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

Pick Qwen2.5 VL 72B Instruct for output tokens 6.0x cheaper ($1.00 vs $6.00 per million).

Model AQwen2.5 VL 72B InstructQwenNot benchmarkedNo coding benchmarkNo cost per solved task Model BQwen3.8 2.4T A95BQwenNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. Qwen2.5 VL 72B Instruct has results on OSWorld, Kagi LLM Benchmark and GeoBench; Qwen3.8 2.4T A95B on AA Coding Index, SciCode and AA Intelligence Index. 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 Qwen3.8 2.4T A95B has a AA Intelligence Index result, 39.9.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.8 2.4T A95B has a AA Agentic Index result, 50.1.
Directional only
Long documents
Listed context window
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 VL 72B Instruct
Qwen2.5 VL 72B Instruct $0.0013, Qwen3.8 2.4T A95B $0.0050 per turn.
List prices

At a glance

Coding index: Qwen2.5 VL 72B Instruct not benchmarked, Qwen3.8 2.4T A95B 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: Qwen2.5 VL 72B Instruct $1.00 against Qwen3.8 2.4T A95B $6.00 per million output tokens, 6.0x apart.
Context window: Qwen2.5 VL 72B Instruct takes 128K tokens, Qwen3.8 2.4T A95B 1.05M.

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 Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B
Benchmark	Qwen2.5 VL 72B Instruct	Qwen3.8 2.4T A95B	Leader
AA Coding Index	Not measured	71.9	Only Qwen3.8 2.4T A95B measured
SciCode	Not measured	54.1%	Only Qwen3.8 2.4T A95B measured
Neither model has a result on the other 41 boards here

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

Intelligence benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B
Benchmark	Qwen2.5 VL 72B Instruct	Qwen3.8 2.4T A95B	Leader
AA Intelligence Index	Not measured	39.9	Only Qwen3.8 2.4T A95B measured
Neither model has a result on the other 1 board here

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

Agentic work benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B
Benchmark	Qwen2.5 VL 72B Instruct	Qwen3.8 2.4T A95B	Leader
AA Agentic Index	Not measured	50.1	Only Qwen3.8 2.4T A95B measured
OSWorld	5.0%	Not measured	Only Qwen2.5 VL 72B Instruct measured
MCP Atlas	Not measured	84.5%	Only Qwen3.8 2.4T A95B measured
Neither model has a result on the other 39 boards here

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

Reasoning benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B
Benchmark	Qwen2.5 VL 72B Instruct	Qwen3.8 2.4T A95B	Leader
GPQA Diamond (Artificial Analysis run)	Not measured	93.5%	Only Qwen3.8 2.4T A95B measured
Humanity's Last Exam (Artificial Analysis run)	Not measured	42.4%	Only Qwen3.8 2.4T A95B measured
Kagi LLM Benchmark	36.0%	Not measured	Only Qwen2.5 VL 72B 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 Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B
Benchmark	Qwen2.5 VL 72B Instruct	Qwen3.8 2.4T A95B	Leader
MathArena	Not measured	31.6%	Only Qwen3.8 2.4T A95B 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 Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B
Benchmark	Qwen2.5 VL 72B Instruct	Qwen3.8 2.4T A95B	Leader
GeoBench	62.0%	Not measured	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 Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B
Benchmark	Qwen2.5 VL 72B Instruct	Qwen3.8 2.4T A95B	Leader
Long context reasoning (AA-LCR)	Not measured	80.3%	Only Qwen3.8 2.4T A95B measured
LMArena Vision	1107	Not measured	Only Qwen2.5 VL 72B Instruct measured
LMArena Vision: English	1115	Not measured	Only Qwen2.5 VL 72B Instruct measured
LMArena Vision: Chinese	1107	Not measured	Only 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

Qwen2.5 VL 72B Instruct$0.0013Fits in one request

Qwen3.8 2.4T A95B$0.0050Fits in one request

Qwen2.5 VL 72B Instruct costs less

Repository review

50K input + 3K output tokens

Qwen2.5 VL 72B Instruct$0.043Fits in one request

Qwen3.8 2.4T A95B$0.118Fits in one request

Qwen2.5 VL 72B Instruct costs less

Agent loop

200K input + 10K output tokens

Qwen2.5 VL 72B Instruct$0.170Exceeds the context window

Qwen3.8 2.4T A95B$0.460Fits in one request

Qwen2.5 VL 72B Instruct 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 Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B
Specification	Qwen2.5 VL 72B Instruct	Qwen3.8 2.4T A95B
Maker	Qwen	Qwen
Weights	Open weights	Open weights
Released	February 1, 2025	August 12, 2026
Context window	128K	1.05M
Input $/Mtok	$0.80	$2.00
Output $/Mtok	$1.00	$6.00
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 Qwen2.5 VL 72B Instruct better than Qwen3.8 2.4T A95B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen2.5 VL 72B Instruct for output tokens 6.0x cheaper ($1.00 vs $6.00 per million).

Which is cheaper, Qwen2.5 VL 72B Instruct or Qwen3.8 2.4T A95B?

Qwen2.5 VL 72B Instruct costs $0.80 per million input tokens and $1.00 per million output tokens; Qwen3.8 2.4T A95B costs $2.00 and $6.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen2.5 VL 72B Instruct or Qwen3.8 2.4T A95B?

Qwen3.8 2.4T A95B, with 1.05M tokens against 128K.

Has any benchmark tested both Qwen2.5 VL 72B Instruct and Qwen3.8 2.4T A95B?

Qwen2.5 VL 72B Instruct or Qwen3.8 2.4T A95B: 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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