Qwen2.5 14B Instruct vs Qwen2.5-VL 72B Instruct
Qwen2.5 14B Instruct comes out ahead, 42 to 30 on our weighted score, and it is the cheaper option too.
- Our pick
Alibaba (Qwen)Qwen2.5 14B Instruct
42/100- ECI—
- Price$0.35 / $1.40
- Context131K
- Alibaba (Qwen)
Qwen2.5-VL 72B Instruct
30/100- ECI—
- Price$2.80 / $8.40
- Context131K
Add a model
Make it a three-way comparison.
Qwen2.5 14B Instruct is our pick
Qwen2.5 14B Instruct is the better all-round choice, scoring 42/100 against Qwen2.5-VL 72B Instruct (30). It leads on price. Qwen2.5-VL 72B Instruct wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen2.5 14B InstructQwen2.5 14B Instruct $0.613 · Qwen2.5-VL 72B Instruct $4.20 per 1M tokens (3:1 blend)
- Longest contextAbout the sameQwen2.5 14B Instruct 131,072 · Qwen2.5-VL 72B Instruct 131,072 tokens
- Widest inputsQwen2.5-VL 72B InstructQwen2.5 14B Instruct: Text · Qwen2.5-VL 72B Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen2.5 14B Instruct | Qwen2.5-VL 72B Instruct |
|---|---|---|---|
| Price | 50% | 60 | 20 |
| Inputs & features | 30% | 25 | 50 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 42/100 | 30/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen2.5 14B InstructAlibaba (Qwen) | Qwen2.5-VL 72B InstructAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.35 (best) | $2.80 |
| Output | $1.40 (best) | $8.40 |
| Cached input | — | — |
| Blended (3:1) | $0.613 (best) | $4.20 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Alibaba API |
| Limits | ||
| Context window | 131,072 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | qwen2-5-14b-instruct | qwen2-5-vl-72b-instruct |
| API providers | 1 | 1 |
| Released | Sep 2024 | Sep 2024 |
| Knowledge cutoff | Apr 2024 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen2.5 14B Instruct$6.30
- Qwen2.5-VL 72B Instruct$44.80
Which should you choose?
Which is better: Qwen2.5 14B Instruct or Qwen2.5-VL 72B Instruct?
Qwen2.5 14B Instruct is the better all-round choice, scoring 42/100 against Qwen2.5-VL 72B Instruct (30). It leads on price. Qwen2.5-VL 72B Instruct wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Qwen2.5 14B Instruct or Qwen2.5-VL 72B Instruct?
Qwen2.5 14B Instruct is cheaper at $0.35 input / $1.40 output per million tokens (official Alibaba API price). Qwen2.5-VL 72B Instruct costs $2.80 input / $8.40 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.613 per million tokens for Qwen2.5 14B Instruct versus $4.20 for Qwen2.5-VL 72B Instruct (6.9× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Qwen2.5 14B Instruct has not been scored yet and Qwen2.5-VL 72B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen2.5 14B Instruct and Qwen2.5-VL 72B Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Qwen2.5 14B Instruct and Qwen2.5-VL 72B Instruct share the same 131,072-token context window. Maximum output per response: Qwen2.5 14B Instruct up to 8,192, Qwen2.5-VL 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Qwen2.5 14B Instruct accepts text; Qwen2.5-VL 72B Instruct accepts text and images. Qwen2.5-VL 72B Instruct handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Qwen2.5 14B Instruct is the newest, released Sep 2024. Qwen2.5-VL 72B Instruct came out Sep 2024. Knowledge cutoff: Qwen2.5 14B Instruct Apr 2024, Qwen2.5-VL 72B Instruct Apr 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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