โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Llama 3.3 70B Instruct vs Qwen-Plus

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Llama 3.3 70B Instruct and Qwen-Plus.

Meta

Llama 3.3 70B Instruct

Meta's state-of-the-art open weights model, providing enterprise-grade reasoning and logic. Exceptionally powerful for self-hosted customer support, text generation, and tooling workflows.

View Full Specs
Alibaba

Qwen-Plus

Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.

View Full Specs

Technical Specifications

SpecificationLlama 3.3 70B InstructQwen-Plus
ProviderMetaAlibaba
Context Window131,072 tokens1,000,000 tokens
Agent Suitability83/100N/A
Time to First Token (TTFT)280 msN/A
Deployment Modelself hostableself hostable
Production Stabilitystablebeta
API AvailableYesYes
Released Date2024-12-062025-02-01

API Pricing Comparison

Input Price per Million Tokens

Llama 3.3 70B Instruct

$0.10

Qwen-Plus

$0.26

Output Price per Million Tokens

Llama 3.3 70B Instruct

$0.32

Qwen-Plus

$0.78

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8620.0%vs8100.0%
Llama 3.3 70B Instruct
Qwen-Plus
HumanEvalPython coding & logic synthesis
8800.0%vs8250.0%
Llama 3.3 70B Instruct
Qwen-Plus
MATHComplex mathematical problem solving
7500.0%vs5500.0%
Llama 3.3 70B Instruct
Qwen-Plus
GPQAGraduate-level expert reasoning
5200.0%vs3700.0%
Llama 3.3 70B Instruct
Qwen-Plus
HellaSwagCommonsense reasoning and inference
8850.0%vs8300.0%
Llama 3.3 70B Instruct
Qwen-Plus
MT-BenchMulti-turn conversation flow quality
880.0%vs865.0%
Llama 3.3 70B Instruct
Qwen-Plus

Llama 3.3 70B Instruct Quirks & Gotchas

  • โ–ธStable, well-documented self-hosted option with strong community support
  • โ–ธOutperformed by Llama 4 Maverick for agentic tool-calling workflows

Qwen-Plus Quirks & Gotchas

No developer gotchas reported.