Which model is better: Llama 3.3 70B Instruct or Qwen 3.8 Flash Next?
Llama 3.3 70B Instruct is 25.0% cheaper for input tokens ($0.12 vs. $0.16 per 1M tokens) and $0.30 vs. $0.47 for output tokens (1.3x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (135ms faster than Qwen 3.8 Flash Next) with 165 vs. 185 tok/s throughput. Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 91.7% vs. 55.6% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.
Zero-Shot RAG Verified
Verified Performance & Unit Economics Delta (12 Dimensions)
Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.
Metric / Dimension
Llama 3.3 70B Instruct
Qwen 3.8 Flash Next
Net Delta / Advantage
Input Cost / 1M Tokens
$0.12
$0.16
Llama 3.3 70B Instruct is 1.3x cheaper
Output Cost / 1M Tokens
$0.30
$0.47
Llama 3.3 70B Instruct (36.2% lower)
Prompt Cache Read / 1M
$0.030
$0.016
Qwen 3.8 Flash Next is 1.9x cheaper
Prompt Cache Write / 1M
$0.12
$0.20
Llama 3.3 70B Instruct is 1.7x cheaper
Context Window (Max Output)
131k (33k out)
268k (66k out)
Qwen 3.8 Flash Next (2.0x larger context)
Avg TTFT Response Latency
145ms
280ms
Llama 3.3 70B Instruct (135ms faster)
Generation Speed (Throughput)
165 tok/s
185 tok/s
Qwen 3.8 Flash Next (+20 tok/s faster)
SWE-bench Verified (Coding)
42.5%
81%
Qwen 3.8 Flash Next (+38.5% lead)
GPQA Diamond (PhD STEM)
55.6%
91.7%
Qwen 3.8 Flash Next (+36.1% lead)
MMLU-Pro (Multi-Discipline)
76.8%
88.4%
Qwen 3.8 Flash Next (+11.6% lead)
MATH-500 (Quantitative Logic)
77%
95.7%
Qwen 3.8 Flash Next (+18.7% lead)
Inference Value Score (IVR)
74.6 / 100
85.1 / 100
Qwen 3.8 Flash Next (+10.5 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Which is cheaper: Llama 3.3 70B Instruct or Qwen 3.8 Flash Next?
Llama 3.3 70B Instruct is cheaper at $0.12/1M input tokens ($0.30/1M output) compared to $0.16/1M input ($0.47/1M output) for Qwen 3.8 Flash Next.
Which model has lower TTFT latency and higher tok/s throughput: Llama 3.3 70B Instruct or Qwen 3.8 Flash Next?
Llama 3.3 70B Instruct delivers faster first-token latency at 145ms TTFT (165 tok/s throughput) compared to 280ms TTFT (185 tok/s) for Qwen 3.8 Flash Next.
How do Llama 3.3 70B Instruct and Qwen 3.8 Flash Next compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Llama 3.3 70B Instruct scores 42.5% versus 81% for Qwen 3.8 Flash Next. On GPQA Diamond graduate-level STEM reasoning, Llama 3.3 70B Instruct scores 55.6% versus 91.7% for Qwen 3.8 Flash Next (and 77% vs 95.7% on MATH-500).
When should you choose Llama 3.3 70B Instruct?
Choose Llama 3.3 70B Instruct (Meta) for cost-optimized on-premise deployments, fast text transformation, structured entity extraction, and enterprise dialogue pipelines — offering a 131k context window, 145ms TTFT, and $0.12/1M input pricing ($0.030/1M cached reads).
When should you choose Qwen 3.8 Flash Next?
Choose Qwen 3.8 Flash Next (Alibaba Cloud) for next-generation open-weight multimodal MoE activating only 6B parameters per token for ultra-low-cost enterprise office automation, tool calling, and multilingual repository engineering — offering a 268k context window, 280ms TTFT, and $0.16/1M input pricing ($0.016/1M cached reads).
