💻 Coding (SWE) WinnerGPT-6.1 Sol 86.4% SWE-bench · 96.8% HumanEval
🧠 STEM Reasoning WinnerGPT-6.1 Sol 92.4% GPQA · 98.8% MATH-500
Which model is better: GPT-6.1 Sol or Llama 4 Maverick?
Llama 4 Maverick is 90.0% cheaper for input tokens ($0.20 vs. $2.00 per 1M tokens) and $0.60 vs. $10.00 for output tokens (10.0x cost advantage). In terms of operational performance, Llama 4 Maverick delivers lower response latency at 135ms TTFT (385ms faster than GPT-6.1 Sol) with 175 vs. 135 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 62.4% for Llama 4 Maverick and 92.4% vs. 73.8% 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
GPT-6.1 Sol
Llama 4 Maverick
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$0.20
Llama 4 Maverick is 10.0x cheaper
Output Cost / 1M Tokens
$10.00
$0.60
Llama 4 Maverick (94.0% lower)
Prompt Cache Read / 1M
$0.100
$0.050
Llama 4 Maverick is 2.0x cheaper
Prompt Cache Write / 1M
$2.00
$0.20
Llama 4 Maverick is 10.0x cheaper
Context Window (Max Output)
1,075k (128k out)
1,049k (33k out)
GPT-6.1 Sol (1.0x larger context)
Avg TTFT Response Latency
520ms
135ms
Llama 4 Maverick (385ms faster)
Generation Speed (Throughput)
135 tok/s
175 tok/s
Llama 4 Maverick (+40 tok/s faster)
SWE-bench Verified (Coding)
86.4%
62.4%
GPT-6.1 Sol (+24.0% lead)
GPQA Diamond (PhD STEM)
92.4%
73.8%
GPT-6.1 Sol (+18.6% lead)
MMLU-Pro (Multi-Discipline)
91%
84.5%
GPT-6.1 Sol (+6.5% lead)
MATH-500 (Quantitative Logic)
98.8%
91%
GPT-6.1 Sol (+7.8% lead)
Inference Value Score (IVR)
62.9 / 100
77 / 100
Llama 4 Maverick (+14.1 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose GPT-6.1 Sol (OpenAI) for delivers near-GPT-6 Astra frontier accuracy at one-fifth the token cost with a 95% cache read discount for high-efficiency agentic coding, computer use, and enterprise workflow automation — offering a 1,075k context window, 520ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).
Which is cheaper: GPT-6.1 Sol or Llama 4 Maverick?
Llama 4 Maverick is cheaper at $0.20/1M input tokens ($0.60/1M output) compared to $2.00/1M input ($10.00/1M output) for GPT-6.1 Sol.
Which model has lower TTFT latency and higher tok/s throughput: GPT-6.1 Sol or Llama 4 Maverick?
Llama 4 Maverick delivers faster first-token latency at 135ms TTFT (175 tok/s throughput) compared to 520ms TTFT (135 tok/s) for GPT-6.1 Sol.
How do GPT-6.1 Sol and Llama 4 Maverick compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-6.1 Sol scores 86.4% versus 62.4% for Llama 4 Maverick. On GPQA Diamond graduate-level STEM reasoning, GPT-6.1 Sol scores 92.4% versus 73.8% for Llama 4 Maverick (and 98.8% vs 91% on MATH-500).
When should you choose GPT-6.1 Sol?
Choose GPT-6.1 Sol (OpenAI) for delivers near-GPT-6 Astra frontier accuracy at one-fifth the token cost with a 95% cache read discount for high-efficiency agentic coding, computer use, and enterprise workflow automation — offering a 1,075k context window, 520ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).
When should you choose Llama 4 Maverick?
Choose Llama 4 Maverick (Meta) for high-throughput open-weight multimodal assistants, enterprise RAG, and low-cost cloud inference on Groq and Cerebras — offering a 1,048k context window, 135ms TTFT, and $0.20/1M input pricing ($0.050/1M cached reads).
