Last verified 2025-09-22 (left) · 2025-09-22 (right)

Claude Haiku 3.5 vs Gemini 2.0 Flash — Pricing & Capability Comparison

Claude Haiku 3.5 charges $0.80 per million input tokens and $4.00 per million output tokens. Gemini 2.0 Flash comes in at $0.10 / $0.40. Context windows span 200K vs 1M tokens respectively.

TL;DR — Quick Comparison

✓Gemini 2.0 Flash is cheaper overall: $0.50 per 1M tokens (in+out) vs $4.80 for Claude Haiku 3.5 — saves $4.30 per 1M tokens
✓Input pricing: Claude Haiku 3.5 $0.80/1M vs Gemini 2.0 Flash $0.10/1M
✓Output pricing: Claude Haiku 3.5 $4.00/1M vs Gemini 2.0 Flash $0.40/1M
✓Context window: Gemini 2.0 Flash offers more (1M vs 200K)
✓Use our calculator below to estimate costs for your specific usage pattern

Input price (per 1M)

Claude Haiku 3.5

$0.80

Gemini 2.0 Flash

$0.10

Gemini 2.0 Flash leads here

Output price (per 1M)

Claude Haiku 3.5

$4.00

Gemini 2.0 Flash

$0.40

Gemini 2.0 Flash leads here

Context window

Claude Haiku 3.5

200,000 tokens

Gemini 2.0 Flash

1,000,000 tokens

Gemini 2.0 Flash leads here

Cached input

Claude Haiku 3.5

Not published

Gemini 2.0 Flash

Not published

No published data

Which one should you choose?

Skip the spreadsheet if you just need the practical takeaway. Use these rules when deciding between Claude Haiku 3.5 and Gemini 2.0 Flash.

Choose Gemini 2.0 Flash if input tokens dominate your bill

Gemini 2.0 Flash has the lower input rate, which usually matters most for chat, RAG, classification, and long-prompt workflows where prompt volume stays much larger than generated output.

Choose Gemini 2.0 Flash if you generate long answers

Gemini 2.0 Flash is cheaper on output tokens, so it tends to win for report generation, coding assistance, reasoning traces, and any workflow where completions are long.

Choose Gemini 2.0 Flash if context size is the blocker

Gemini 2.0 Flash offers the larger published context window, which is more important than small pricing differences when you need to fit large files, long chats, or multi-document prompts into one request.

Cost comparison for 10K-token workloads

Side-by-side pricing for identical workloads (10,000 total tokens per request) across different distributions.

Scenario	Claude Haiku 3.5	Gemini 2.0 Flash
Balanced conversation 50% input · 50% output	$0.0240	$0.0025
Input-heavy workflow 80% input · 20% output	$0.0144	$0.0016
Generation heavy 30% input · 70% output	$0.0304	$0.0031
Cached system prompt 90% cached input · 10% fresh output	$0.0112	$0.0013

Frequently asked questions

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

Gemini 2.0 Flash is cheaper for input tokens at $0.10 per 1M tokens compared to $0.80. For output, Gemini 2.0 Flash costs $0.40 per 1M tokens versus $4.00 for Claude Haiku 3.5.

What is the cost per 1M tokens for Claude Haiku 3.5?

Claude Haiku 3.5 pricing: $0.80 per 1M input tokens and $4.00 per 1M output tokens. Context window: 200,000 tokens.

What is the cost per 1M tokens for Gemini 2.0 Flash?

Gemini 2.0 Flash pricing: $0.10 per 1M input tokens and $0.40 per 1M output tokens. Context window: 1,000,000 tokens.

How much does it cost per 1K tokens?

Per 1K tokens: Claude Haiku 3.5 costs $0.0008 input / $0.0040 output. Gemini 2.0 Flash costs $0.0001 input / $0.0004 output. This is useful for calculating small-scale usage costs.

Which model supports a larger context window?

Gemini 2.0 Flash offers 1,000,000 tokens (1M) versus 200K for Claude Haiku 3.5.

What is the estimated monthly cost for typical usage?

For a typical workload of 10M input + 2M output tokens per month: Claude Haiku 3.5 would cost approximately $16.00, while Gemini 2.0 Flash would cost $1.80. Gemini 2.0 Flash is more economical for this usage pattern.

Do these models support prompt caching?

Claude Haiku 3.5 does not publish cached pricing. Gemini 2.0 Flash does not publish cached pricing.

Which model is best for my use case?

Choose Gemini 2.0 Flash for cost-sensitive applications with high input volume. Choose Gemini 2.0 Flash if you need 1M context for long documents or conversations. Consider prompt caching if you have repeated context. Use our token calculator to model your specific usage pattern.