💰 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 Qwen 3.8 Flash Next 81% SWE-bench · 95.1% HumanEval
🧠 STEM Reasoning Winner Qwen 3.8 Flash Next 91.7% GPQA · 95.7% MATH-500

Which model is better: Gemini 2.0 Flash or Qwen 3.8 Flash Next?

Gemini 2.0 Flash excels in speed and cost efficiency, while Qwen3.8-Flash-Next dominates reasoning and coding benchmarks. Gemini is 37.5% cheaper on input ($0.10 vs. $0.16 per 1M tokens), 920ms faster at 280ms TTFT, and hits 185 vs. 65 tok/s. Conversely, Qwen3.8-Flash-Next leads SWE-bench Verified (81.0% vs. 51.8%) and GPQA Diamond (91.7% vs. 63.6%).
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 Qwen 3.8 Flash Next Net Delta / Advantage
Input Cost / 1M Tokens $0.10 $0.16 Gemini 2.0 Flash is 1.6x cheaper
Output Cost / 1M Tokens $0.40 $0.47 Gemini 2.0 Flash (14.9% lower)
Prompt Cache Read / 1M $0.025 $0.016 Qwen 3.8 Flash Next is 1.6x cheaper
Prompt Cache Write / 1M $0.10 $0.20 Gemini 2.0 Flash is 2.0x cheaper
Context Window (Max Output) 1,073k (8k out) 268k (66k out) Gemini 2.0 Flash (4.0x larger context)
Avg TTFT Response Latency 280ms 280ms Identical Latency
Generation Speed (Throughput) 185 tok/s 185 tok/s Equal Throughput
SWE-bench Verified (Coding) 51.8% 81% Qwen 3.8 Flash Next (+29.2% lead)
GPQA Diamond (PhD STEM) 63.6% 91.7% Qwen 3.8 Flash Next (+28.1% lead)
MMLU-Pro (Multi-Discipline) 78.2% 88.4% Qwen 3.8 Flash Next (+10.2% lead)
MATH-500 (Quantitative Logic) 91.1% 95.7% Qwen 3.8 Flash Next (+4.6% lead)
Inference Value Score (IVR) 77.7 / 100 85.1 / 100 Qwen 3.8 Flash Next (+7.4 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

Qwen 3.8 Flash Next $4.55

$0.16/1M in · $0.47/1M out

Prompt Cache: $0.016/1M read · $0.20/1M write

Projected Monthly Cost Reduction
$0.99 / mo
(21.7% 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 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).

Related Questions & Decision Factors

Which is cheaper: Gemini 2.0 Flash or Qwen 3.8 Flash Next?

Gemini 2.0 Flash is cheaper at $0.10/1M input tokens ($0.40/1M 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: Gemini 2.0 Flash or Qwen 3.8 Flash Next?

Both Gemini 2.0 Flash and Qwen 3.8 Flash Next deliver comparable response times around 280ms TTFT.

How do Gemini 2.0 Flash and Qwen 3.8 Flash Next compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Gemini 2.0 Flash scores 51.8% versus 81% for Qwen 3.8 Flash Next. On GPQA Diamond graduate-level STEM reasoning, Gemini 2.0 Flash scores 63.6% versus 91.7% for Qwen 3.8 Flash Next (and 91.1% vs 95.7% 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 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).

Explore High-Priority Related Model Matchups