Model profile
Alibaba

Qwen2.5 72B Instruct

Qwen2.5 72B Instruct is a budget-priced text-first model from Alibaba with balanced runtime profile, standard context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsBalanced latencyStandard contextBudget pricing
Intelligence
15.6

Benchmark blend

Coding
11.9

Dev workflow signal

Context
33K Tokens

Standard

Input Price
$0.00

Budget tier

Decision snapshot
39

Qwen2.5 72B Instruct currently reads as a budget text-first option with standard context and a balanced runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Agent workflows
Latency tier
Balanced
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
15.6
16

General reasoning and benchmark headroom.

Limited
Speed
54 tok/s
59

TTFT 1.08s

Competitive
Context
33K Tokens
48

How much prompt and task state can stay in view.

Situational
Price
$0.00
86

$0.00 output / 1M

Efficient

Editorial Profile

Qwen2.5 72B Instruct in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score 12Math score 14

Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...

Identity

Alibaba text-first profile

Positioning

Long-context research / Agent workflows with standard context and balanced runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • The available source data suggests a balanced profile rather than one dominant edge.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency is balanced rather than ultra-fast, which is fine for most workflows but not the snappiest tier.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

  • Context window is more comfortable for focused tasks than extremely long sessions.

Best fit
  • Focused chat, retrieval-augmented flows, and narrower production tasks.

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Context
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
15.6
MMLU Pro
72.0%
GPQA
49.1%
HLE
4.2%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
11.9
LiveCodeBench
0.276
SciCode
26.7%
Math

Formal reasoning, structured problem solving, and competition-style math.

Math Index
14.0
AIME
16.0%
AIME 2025
14.0%
Math 500
85.8%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
36.9%
TAU2
34.5%
TerminalBench Hard
4.5%
LCR
20.3%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
33K Tokens
Vision
Text-first
Modalities
text
Tokenizer
Qwen
Max Completion
16384
Moderation
No
Supported Parameters
frequency_penaltymax_tokensmin_ppresence_penaltyrepetition_penaltyresponse_formatseedstoptemperaturetool_choicetoolstop_ktop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.00
Output
per 1M output tokens
$0.00
Blended
AA 3:1 mix
$0.00

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.