Model Comparison

Llama 3.3 70B Instruct vs Qwen3 VL 8B Thinking

Both models are evenly matched across the benchmarks. Llama 3.3 70B Instruct is 3.3x cheaper per token.

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

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.

Wed May 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.3 70B Instruct costs less

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

Lowest available price from all providers
Wed May 13 2026 • llm-stats.com
Meta
Llama 3.3 70B Instruct
Input tokens$0.20
Output tokens$0.20
Best providerLambda
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
Input tokens$0.18
Output tokens$2.09
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

61.0B diff

Llama 3.3 70B Instruct has 61.0B more parameters than Qwen3 VL 8B Thinking, making it 677.8% larger.

Meta
Llama 3.3 70B Instruct
70.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
9.0Bparameters
70.0B
Llama 3.3 70B Instruct
9.0B
Qwen3 VL 8B Thinking

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.

Meta
Llama 3.3 70B Instruct
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
Input262,144 tokens
Output262,144 tokens
Wed May 13 2026 • llm-stats.com

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

Text
Images
Audio
Video

Qwen3 VL 8B Thinking

Text
Images
Audio
Video

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 70B Instruct

Llama 3.3 Community License Agreement

Open weights

Qwen3 VL 8B Thinking

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.

Llama 3.3 70B Instruct

Dec 6, 2024

1.4 years ago

Qwen3 VL 8B Thinking

Sep 22, 2025

7 months ago

9mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

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

lambda logo
Lambda
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.23/1MOutput Price:Output: $0.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M
groq logo
Groq
Input Price:Input: $0.59/1MOutput Price:Output: $7.90/1M
sambanova logo
Sambanova
Input Price:Input: $0.60/1MOutput Price:Output: $1.20/1M
cerebras logo
Cerebras
Input Price:Input: $0.70/1MOutput Price:Output: $0.80/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
together logo
Together
Input Price:Input: $0.88/1MOutput Price:Output: $0.88/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

Qwen3 VL 8B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $2.09/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Less expensive output tokens
Higher IFEval score (92.1% vs 83.2%)
Higher MMLU score (86.0% vs 85.2%)
Alibaba Cloud / Qwen Team

Qwen3 VL 8B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Supports multimodal inputs
Less expensive input tokens
Higher GPQA score (69.9% vs 50.5%)
Higher MMLU-Pro score (77.3% vs 68.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Meta
Llama 3.3 70B Instruct
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking

FAQ

Common questions about Llama 3.3 70B Instruct vs Qwen3 VL 8B Thinking.

Which is better, Llama 3.3 70B Instruct or Qwen3 VL 8B Thinking?

Both models are evenly matched across the benchmarks. Llama 3.3 70B Instruct is made by Meta and Qwen3 VL 8B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Llama 3.3 70B Instruct compare to Qwen3 VL 8B Thinking in benchmarks?

Llama 3.3 70B Instruct scores IFEval: 92.1%, MGSM: 91.1%, HumanEval: 88.4%, MBPP EvalPlus: 87.6%, MMLU: 86.0%. Qwen3 VL 8B Thinking scores DocVQAtest: 95.3%, ScreenSpot: 93.6%, MMLU-Redux: 88.8%, MMBench-V1.1: 87.5%, InfoVQAtest: 86.0%.

Is Llama 3.3 70B Instruct cheaper than Qwen3 VL 8B Thinking?

Qwen3 VL 8B Thinking is 1.1x cheaper for input tokens. Llama 3.3 70B Instruct costs $0.20/M input and $0.20/M output via lambda. Qwen3 VL 8B Thinking costs $0.18/M input and $2.09/M output via deepinfra.

What are the context window sizes for Llama 3.3 70B Instruct and Qwen3 VL 8B Thinking?

Llama 3.3 70B Instruct supports 128K tokens and Qwen3 VL 8B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama 3.3 70B Instruct and Qwen3 VL 8B Thinking?

Key differences include context window (128K vs 262K), input pricing ($0.20 vs $0.18/M), multimodal support (no vs yes), licensing (Llama 3.3 Community License Agreement vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.3 70B Instruct and Qwen3 VL 8B Thinking?

Llama 3.3 70B Instruct is developed by Meta and Qwen3 VL 8B Thinking is developed by Alibaba Cloud / Qwen Team.