💰 Unit Cost Winner Gemini 2.0 Flash $0.10/1M in · $0.40/1M out
⚡ Latency & Speed Winner Gemini 2.0 Flash 280ms TTFT · 185 tok/s
💻 Coding (SWE) Winner GPT-6 Astra 75.7% SWE-bench · 96.8% HumanEval
🧠 STEM Reasoning Winner GPT-6 Astra 96% GPQA · 98% MATH-500

Which model is better: Gemini 2.0 Flash or GPT-6 Astra?

Gemini 2.0 Flash is 99.0% cheaper for input tokens ($0.10 vs. $10.00 per 1M tokens) and $0.40 vs. $50.00 for output tokens (100.0x cost advantage). In terms of operational performance, Gemini 2.0 Flash delivers lower response latency at 280ms TTFT (460ms faster than GPT-6 Astra) with 185 vs. 74 tok/s throughput. GPT-6 Astra leads coding evaluations at 75.7% SWE-bench Verified vs. 51.8% for Gemini 2.0 Flash and 96.0% vs. 63.6% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.

Verified Performance & Unit Economics Delta (12 Dimensions)

Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.

Metric / Dimension Gemini 2.0 Flash GPT-6 Astra Net Delta / Advantage
Input Cost / 1M Tokens $0.10 $10.00 Gemini 2.0 Flash is 100.0x cheaper
Output Cost / 1M Tokens $0.40 $50.00 Gemini 2.0 Flash (99.2% lower)
Prompt Cache Read / 1M $0.025 $1.000 Gemini 2.0 Flash is 40.0x cheaper
Prompt Cache Write / 1M $0.10 $12.50 Gemini 2.0 Flash is 125.0x cheaper
Context Window (Max Output) 1,073k (8k out) 1,075k (128k out) GPT-6 Astra (1.0x larger context)
Avg TTFT Response Latency 280ms 740ms Gemini 2.0 Flash (460ms faster)
Generation Speed (Throughput) 185 tok/s 74 tok/s Gemini 2.0 Flash (+111 tok/s faster)
SWE-bench Verified (Coding) 51.8% 75.7% GPT-6 Astra (+23.9% lead)
GPQA Diamond (PhD STEM) 63.6% 96% GPT-6 Astra (+32.4% lead)
MMLU-Pro (Multi-Discipline) 78.2% 91.2% GPT-6 Astra (+13.0% lead)
MATH-500 (Quantitative Logic) 91.1% 98% GPT-6 Astra (+6.9% lead)
Inference Value Score (IVR) 77.7 / 100 47.6 / 100 Gemini 2.0 Flash (+30.1 pts)

Interactive Monthly Token Economics & ROI Forecaster

Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.

25.0M Tokens
500K 50M 250M 500M+
5.0M Tokens
100K 25M 75M 150M+
50% Cached
0% (Uncached) 25% 50% (Typical Agent) 95% Max

Estimated Monthly Spend

Gemini 2.0 Flash $3.56

$0.10/1M in · $0.40/1M out

Prompt Cache: $0.025/1M read · $0.10/1M write

GPT-6 Astra $387.50

$10.00/1M in · $50.00/1M out

Prompt Cache: $1.000/1M read · $12.50/1M write

Projected Monthly Cost Reduction
$383.94 / mo
(99.1% lower cost with Gemini 2.0 Flash)
Open Full Matchup Analysis →
A

When to Choose Gemini 2.0 Flash

Choose Gemini 2.0 Flash (Google DeepMind) for legacy high-throughput multimodal pipelines migrating to Gemini 3.8 Flash — offering a 1,073k context window, 280ms TTFT, and $0.10/1M input pricing ($0.025/1M cached reads).

B

When to Choose GPT-6 Astra

Choose GPT-6 Astra (OpenAI) for high-autonomy flagship reasoning model engineered for end-to-end computer and browser use, advanced scientific research, and complex multi-turn software engineering — offering a 1,075k context window, 740ms TTFT, and $10.00/1M input pricing ($1.000/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Gemini 2.0 Flash or GPT-6 Astra?

Gemini 2.0 Flash is cheaper at $0.10/1M input tokens ($0.40/1M output) compared to $10.00/1M input ($50.00/1M output) for GPT-6 Astra.

Which model has lower TTFT latency and higher tok/s throughput: Gemini 2.0 Flash or GPT-6 Astra?

Gemini 2.0 Flash delivers faster first-token latency at 280ms TTFT (185 tok/s throughput) compared to 740ms TTFT (74 tok/s) for GPT-6 Astra.

How do Gemini 2.0 Flash and GPT-6 Astra compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Gemini 2.0 Flash scores 51.8% versus 75.7% for GPT-6 Astra. On GPQA Diamond graduate-level STEM reasoning, Gemini 2.0 Flash scores 63.6% versus 96% for GPT-6 Astra (and 91.1% vs 98% on MATH-500).

When should you choose Gemini 2.0 Flash?

Choose Gemini 2.0 Flash (Google DeepMind) for legacy high-throughput multimodal pipelines migrating to Gemini 3.8 Flash — offering a 1,073k context window, 280ms TTFT, and $0.10/1M input pricing ($0.025/1M cached reads).

When should you choose GPT-6 Astra?

Choose GPT-6 Astra (OpenAI) for high-autonomy flagship reasoning model engineered for end-to-end computer and browser use, advanced scientific research, and complex multi-turn software engineering — offering a 1,075k context window, 740ms TTFT, and $10.00/1M input pricing ($1.000/1M cached reads).

Explore High-Priority Related Model Matchups