Model Comparison
Llama 3.3 70B Instruct vs Qwen3 VL 8B ThinkingWhich is better in 2026?
Both models are evenly matched across the benchmarks. Llama 3.3 70B Instruct is 3.3x cheaper per token.
Verdict: Llama 3.3 70B Instruct vs Qwen3 VL 8B Thinking — which is better?
Llama 3.3 70B Instruct (by Meta) and Qwen3 VL 8B Thinking (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Llama 3.3 70B Instruct outperforms in 2 benchmarks (IFEval, MMLU), while Qwen3 VL 8B Thinking is better at 2 benchmarks (GPQA, MMLU-Pro). Both models are evenly matched across the benchmarks.
On price, Llama 3.3 70B Instruct is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 8B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Choose Llama 3.3 70B Instruct if…
- cost matters — it's about 3.3x cheaper per token
Choose Qwen3 VL 8B Thinking if…
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
Llama 3.3 70B Instruct outperforms in 2 benchmarks (IFEval, MMLU), while Qwen3 VL 8B Thinking is better at 2 benchmarks (GPQA, MMLU-Pro).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 3.3 70B Instruct ($0.20/1M tokens) is 1.1x more expensive than Qwen3 VL 8B Thinking ($0.18/1M tokens).
For output processing, Llama 3.3 70B Instruct ($0.20/1M tokens) is 10.4x cheaper than Qwen3 VL 8B Thinking ($2.09/1M tokens).
In conclusion, Qwen3 VL 8B Thinking is more expensive than Llama 3.3 70B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 3.3 70B Instruct has 61.0B more parameters than Qwen3 VL 8B Thinking, making it 677.8% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 8B Thinking accepts 262,144 input tokens compared to Llama 3.3 70B Instruct's 128,000 tokens. Qwen3 VL 8B Thinking can generate longer responses up to 262,144 tokens, while Llama 3.3 70B Instruct is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 8B Thinking supports multimodal inputs, whereas Llama 3.3 70B Instruct does not.
Qwen3 VL 8B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Llama 3.3 70B Instruct
Qwen3 VL 8B Thinking
License
Usage and distribution terms
Llama 3.3 70B Instruct is licensed under Llama 3.3 Community License Agreement, while Qwen3 VL 8B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.3 Community License Agreement
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Llama 3.3 70B Instruct was released on 2024-12-06, while Qwen3 VL 8B Thinking was released on 2025-09-22.
Qwen3 VL 8B Thinking is 10 months newer than Llama 3.3 70B Instruct.
Dec 6, 2024
1.5 years ago
Sep 22, 2025
8 months ago
9mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 3.3 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks. Qwen3 VL 8B Thinking is available from DeepInfra.
Llama 3.3 70B Instruct
Qwen3 VL 8B Thinking
Outputs Comparison
Key Takeaways
Qwen3 VL 8B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Llama 3.3 70B Instruct vs Qwen3 VL 8B Thinking.