Qwen2-VL-7B-Instruct: benchmark scores, price and ranking

Qwen2-VL-7B-Instruct from Alibaba ranks #514 of 743 LLMs on the LLMs Tiger aggregate benchmark score (46.5), based on 1 benchmark results captured up to 2026-10-13.

Organisation: Alibaba
Type: Open-weight / local model
Open weights: Yes
Released: 2024-08-29 (source: epoch)
Cheapest API price: $0.020 in / $0.060 out per million tokens (via nebius, observed 2026-10-13T21:47Z)
Aggregate rank: #514 of 743 (score 46.5)

Across the 1 benchmark where at least ten models are scored, Qwen2-VL-7B-Instruct is in the top 10% on 0 and in the top half on 0.

Its cheapest listed input price, $0.020 per million tokens, is lower than that of 97% of the 427 models with a listed price.

Qwen2-VL-7B-Instruct benchmark results

Qwen2-VL-7B-Instruct benchmark scores, ranked against all models measured on each benchmark
Benchmark	Score	Rank	Source	Captured
BALROG	3.7%	#34 of 34	Epoch AI Benchmarking Hub	2026-10-13

About Qwen2-VL-7B-Instruct

Qwen2-VL-7B-Instruct is an open-weight model that can run on your own hardware from Alibaba. It was released on 2024-08-29, according to Epoch AI. The cheapest API listing we track charges $0.020 per million input tokens and $0.060 per million output tokens, through nebius. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.

Where Qwen2-VL-7B-Instruct stands

On our aggregate score, Qwen2-VL-7B-Instruct is #514 of 743 ranked models, in the lower half. Its score is 46.5; the scale is centred on 50, so it sits 3.5 points below the typical model. That beats 31% of the ranked field. Among the 74 ranked Alibaba models it is #51. The next one up is Qwen2.5-Coder-3B-Instruct at 46.5. The next one down is Qwen2.5-7B at 46.5.

Qwen2-VL-7B-Instruct, benchmark by benchmark

BALROG is a weak spot. Qwen2-VL-7B-Instruct scores 3.7%, #34 of 34, behind 97% of the models measured. The leader, GPT-6 Astra (max), reaches 68.3%. It covers long-horizon game-playing agents. The board median is 27.6%, so Qwen2-VL-7B-Instruct is 23.9 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

Price and value

The median input price across the 427 priced models is $0.500 per million tokens, so Qwen2-VL-7B-Instruct costs less than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on gpt-oss-120b (high) ($0.030) and Llama 3.1-8B ($0.030).

Release history

The Alibaba model released before it was Qwen2-VL-72B-Instruct on 2024-08-29, which scores 47.6. The next one was ollama/qwen2.5:32b on 2024-09-17, at 48.9.

Reading these numbers

The 1 score on this page comes from 1 source: Epoch AI Benchmarking Hub (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 1 results the aggregate rank can move a lot when one new score arrives.

Models ranked nearby

#511 amazon.nova-pro-v1:0 (46.5)
#512 aya-expanse-32b (46.5)
#513 Mistral Small 4 (46.5)
#515 Gemma 2 9B (46.5)
#516 deepseek-chat (46.5)
#517 Qwen2.5-7B (46.5)