💰 Unit Cost Winner Gemini 2.0 Flash $0.10/1M in · $0.40/1M out
⚡ Latency & Speed Winner Claude 3.5 Haiku 190ms TTFT · 130 tok/s
💻 Coding (SWE) Winner Gemini 2.0 Flash 51.8% SWE-bench · 90.7% HumanEval
🧠 STEM Reasoning Winner Gemini 2.0 Flash 63.6% GPQA · 91.1% MATH-500

Which model is better: Claude 3.5 Haiku or Gemini 2.0 Flash?

Gemini 2.0 Flash is 87.5% cheaper for input tokens ($0.10 vs. $0.80 per 1M tokens) and $0.40 vs. $4.00 for output tokens (8.0x cost advantage). In terms of operational performance, Claude 3.5 Haiku delivers lower response latency at 190ms TTFT (90ms faster than Gemini 2.0 Flash) with 130 vs. 185 tok/s throughput. Gemini 2.0 Flash leads coding evaluations at 51.8% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 63.6% vs. 41.6% 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 Claude 3.5 Haiku Gemini 2.0 Flash Net Delta / Advantage
Input Cost / 1M Tokens $0.80 $0.10 Gemini 2.0 Flash is 8.0x cheaper
Output Cost / 1M Tokens $4.00 $0.40 Gemini 2.0 Flash (90.0% lower)
Prompt Cache Read / 1M $0.080 $0.025 Gemini 2.0 Flash is 3.2x cheaper
Prompt Cache Write / 1M $1.00 $0.10 Gemini 2.0 Flash is 10.0x cheaper
Context Window (Max Output) 205k (8k out) 1,073k (8k out) Gemini 2.0 Flash (5.2x larger context)
Avg TTFT Response Latency 190ms 280ms Claude 3.5 Haiku (90ms faster)
Generation Speed (Throughput) 130 tok/s 185 tok/s Gemini 2.0 Flash (+55 tok/s faster)
SWE-bench Verified (Coding) 40.6% 51.8% Gemini 2.0 Flash (+11.2% lead)
GPQA Diamond (PhD STEM) 41.6% 63.6% Gemini 2.0 Flash (+22.0% lead)
MMLU-Pro (Multi-Discipline) 71% 78.2% Gemini 2.0 Flash (+7.2% lead)
MATH-500 (Quantitative Logic) 69.4% 91.1% Gemini 2.0 Flash (+21.7% lead)
Inference Value Score (IVR) 52.4 / 100 77.7 / 100 Gemini 2.0 Flash (+25.3 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

Claude 3.5 Haiku $31.00

$0.80/1M in · $4.00/1M out

Prompt Cache: $0.080/1M read · $1.00/1M write

Gemini 2.0 Flash $3.56

$0.10/1M in · $0.40/1M out

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

Projected Monthly Cost Reduction
$27.44 / mo
(88.5% lower cost with Gemini 2.0 Flash)
Open Full Matchup Analysis →
A

When to Choose Claude 3.5 Haiku

Choose Claude 3.5 Haiku (Anthropic) for rapid customer-facing chat, sub-agent routing, and real-time code autocomplete — offering a 204k context window, 190ms TTFT, and $0.80/1M input pricing ($0.080/1M cached reads).

B

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).

Related Questions & Decision Factors

Which is cheaper: Claude 3.5 Haiku or Gemini 2.0 Flash?

Gemini 2.0 Flash is cheaper at $0.10/1M input tokens ($0.40/1M output) compared to $0.80/1M input ($4.00/1M output) for Claude 3.5 Haiku.

Which model has lower TTFT latency and higher tok/s throughput: Claude 3.5 Haiku or Gemini 2.0 Flash?

Claude 3.5 Haiku delivers faster first-token latency at 190ms TTFT (130 tok/s throughput) compared to 280ms TTFT (185 tok/s) for Gemini 2.0 Flash.

How do Claude 3.5 Haiku and Gemini 2.0 Flash compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Claude 3.5 Haiku scores 40.6% versus 51.8% for Gemini 2.0 Flash. On GPQA Diamond graduate-level STEM reasoning, Claude 3.5 Haiku scores 41.6% versus 63.6% for Gemini 2.0 Flash (and 69.4% vs 91.1% on MATH-500).

When should you choose Claude 3.5 Haiku?

Choose Claude 3.5 Haiku (Anthropic) for rapid customer-facing chat, sub-agent routing, and real-time code autocomplete — offering a 204k context window, 190ms TTFT, and $0.80/1M input pricing ($0.080/1M cached reads).

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).

Explore High-Priority Related Model Matchups