Qwen-VL OCR vs Llama 3.1 Nemotron 70B Instruct
Llama 3.1 Nemotron 70B Instruct comes out ahead, 45 to 36 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)
Qwen-VL OCR
36/100- ECI—
- Price$0.72 / $0.72
- Context34K
- Our pick
NVIDIA
Llama 3.1 Nemotron 70B Instruct
45/100- ECI—
- Price$0.478 / $0.504
- Context128K
Add a model
Make it a three-way comparison.
Llama 3.1 Nemotron 70B Instruct is our pick
Llama 3.1 Nemotron 70B Instruct is the better all-round choice, scoring 45/100 against Qwen-VL OCR (36). It leads on price and context window. 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 priceLlama 3.1 Nemotron 70B InstructLlama 3.1 Nemotron 70B Instruct $0.485 · Qwen-VL OCR $0.72 per 1M tokens (3:1 blend)
- Longest contextLlama 3.1 Nemotron 70B InstructLlama 3.1 Nemotron 70B Instruct 128,000 · Qwen-VL OCR 34,096 tokens
- Widest inputsQwen-VL OCRQwen-VL OCR: Text, Images · Llama 3.1 Nemotron 70B Instruct: Text
- Self-hostingLlama 3.1 Nemotron 70B InstructPublishes downloadable weights
| Measure | Weight | Qwen-VL OCR | Llama 3.1 Nemotron 70B Instruct |
|---|---|---|---|
| Price | 50% | 57 | 65 |
| Inputs & features | 30% | 25 | 25 |
| Context window | 20% | 1 | 24 |
| Overall | 100% | 36/100 | 45/100 |
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 | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.72 | $0.478 (best) |
| Output | $0.72 | $0.504 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.72 | $0.485 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 2 providers |
| Limits | ||
| Context window | 34,096 tokens | 128,000 tokens (best) |
| Max output | 4,096 tokens | 8,192 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | No | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | qwen-vl-ocr | nvidia/llama-3.1-nemotron-70b-instruct |
| API providers | 1 | 3 (best) |
| Released | Oct 28, 2024 | Apr 15, 2025 |
| Knowledge cutoff | 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.
Qwen-VL OCR$8.64
Llama 3.1 Nemotron 70B Instruct$5.79
Which should you choose?
Which is better: Qwen-VL OCR or Llama 3.1 Nemotron 70B Instruct?
Llama 3.1 Nemotron 70B Instruct is the better all-round choice, scoring 45/100 against Qwen-VL OCR (36). It leads on price and context window. 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, Qwen-VL OCR or Llama 3.1 Nemotron 70B Instruct?
Llama 3.1 Nemotron 70B Instruct is cheaper at $0.478 input / $0.504 output per million tokens (median across 2 API providers; free on Nvidia). Qwen-VL OCR costs $0.72 input / $0.72 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.485 per million tokens for Llama 3.1 Nemotron 70B Instruct versus $0.72 for Qwen-VL OCR (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Qwen-VL OCR has not been scored yet and Llama 3.1 Nemotron 70B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen-VL OCR and Llama 3.1 Nemotron 70B Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-VL OCR does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama 3.1 Nemotron 70B Instruct has the largest context window at 128,000 tokens, against 34,096 for Qwen-VL OCR. Maximum output per response: Qwen-VL OCR up to 4,096, Llama 3.1 Nemotron 70B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Qwen-VL OCR accepts text and images; Llama 3.1 Nemotron 70B Instruct accepts text. Qwen-VL OCR handles the widest range of inputs.
Are any of these open source?
Llama 3.1 Nemotron 70B Instruct publishes its weights and can be self-hosted; Qwen-VL OCR is proprietary.
Which is newer?
Llama 3.1 Nemotron 70B Instruct is the newest, released Apr 15, 2025. Qwen-VL OCR came out Oct 28, 2024. Knowledge cutoff: Qwen-VL OCR 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.