Gemini 3.8 Flash API Cost in TWD: Same Price, More Tokens

Query date: 2026-09-20 (Taipei time). Benchmark data comes from the Artificial Analysis API in real time. Pricing follows the USD unit prices shown on the BazaarLink models page, and the exchange rate is 1 USD = NT$ 31.5 (consistent with the other price articles on the site).

Gemini 3.8 Flash is the new Flash-series version Google released on 2026-09-02. After its listing on BazaarLink, you can call it directly with the model name gemini-3.8-flash. Google's positioning is clear: it is not a new base model, but an enhancement over 3.7 Flash aimed at long-running software engineering and autonomous agents. On complex tasks, it runs more reasoning steps and calls tools more repeatedly.

Bottom line up front: 3.8 Flash has exactly the same unit price as 3.7 Flash (input $0.75 / output $3.75 per million tokens). Its intelligence index rises from 39.1 to 40.9, and agent and long-running task performance improves noticeably. However, it burns more reasoning tokens on hard problems (we measured an average of +22%), so the actual cost per task is higher than with 3.7. On short tasks the two barely differ; the switch is only worth it for long-running agent tasks.

Want to call Gemini 3.8 Flash and pay in TWD with a unified invoice that carries your tax ID? BazaarLink offers an OpenAI-compatible route with the same model unit prices, plus a 10% top-up service fee, addressing the expense-reporting pain point for Taiwan companies. See the complete guide to AI API expense reporting for Taiwan companies for details.

Third-party benchmark: Artificial Analysis

(Data from the Artificial Analysis API, query date 2026-09-20, using the high reasoning setting)

Two numbers are worth noting. First, the Coding Index differs by only 0.2, so coding quality itself has not changed; the gains are concentrated in the intelligence index (+1.8) and Google's own published long-running agent benchmark (Terminal-Bench 2.1, from 81.6% to 90.8%). Second, time to first token rises from 7.1 seconds to 10.0 seconds. This is the cost of "thinking more," so watch out for latency-sensitive real-time scenarios.

Price comparison (USD ↔ NT$)

The prices in this table match the BazaarLink models page, with no model markup. For the latest unit prices, see BazaarLink Models. For TWD prices across the full Gemini lineup, see Gemini API TWD cost estimate 2026.

Same price, different bill: 3.8 Flash thinks more on hard problems

This is the point most often overlooked when choosing a model. We ran the same set of questions 20 times each against 3.8 Flash and 3.7 Flash, recording the reasoning token counts returned by the upstream:

On hard problems it burns 22% more on average, while short-answer questions show no difference (or slightly fewer). This matches Google's description: 3.8 Flash "works harder" and only adds reasoning steps on complex tasks. So at the same unit price, whether your monthly bill changes depends on which type of task you send it.

Scenario estimate: multi-step agent tasks (NT$/month)

Assumptions: 200 agent tasks per day (multi-step, calling tools), 6,000 input tokens per call. 3.7 Flash produces about 2,000 output tokens per call, and 3.8 Flash is estimated at 2,440 tokens (+22% per the table above).

• Monthly tasks: 200 × 30 = 6,000 calls
• Monthly input: 6,000 × 6,000 = 36 MTok (same for both)
• Monthly output: 3.7 Flash 12 MTok; 3.8 Flash 14.6 MTok

Cost:

• 3.7 Flash: 36 × NT$ 24 + 12 × NT$ 118 = NT$ 864 + NT$ 1,418 = NT$ 2,282/month
• 3.8 Flash: 36 × NT$ 24 + 14.6 × NT$ 118 = NT$ 864 + NT$ 1,725 = NT$ 2,589/month

→ About NT$ 300/month more (+13%), in exchange for agent tasks being less often abandoned midway (Google's published long-running benchmark: +9 percentage points). If your failure mode is exactly "the agent stalls halfway," that money is worth it; if not, 3.8 Flash will not fix your problem.

Specs

• Context length: 1,048,576 tokens
• Input: text, images, files, audio, video; output: text
• Deep reasoning, with support for structured output and tool calling
• Model ID: gemini-3.8-flash (compatibility alias: google/gemini-3.8-flash)

How to call it

curl https://bazaarlink.ai/api/v1/chat/completions \
  -H "Authorization: Bearer sk-bl-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.8-flash",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

OpenAI SDK compatible; just change base_url and model, no other code changes needed. To migrate from 3.7 Flash, only change the model string; the parameters are identical.

When to choose 3.8 Flash, and when not to

Good fit:

• Long-running agents, multi-step tool calls, automated software engineering tasks: this is the main arena Google designed it for
• Specialized fields such as finance and law that need multi-step analysis and report generation

Not a good fit (stay on 3.7 Flash):

• Short tasks such as chat, classification, extraction, and translation: the two perform almost the same, and 3.8 has no advantage
• Real-time interaction sensitive to first-token latency: 3.8 Flash's first-token latency is about 3 seconds longer
• Existing, stable workflows where efficiency is the priority: Google itself recommends keeping this kind of work on 3.7 Flash

Sources and query log

• Artificial Analysis: Gemini 3.8 Flash model page (query date 2026-09-20)
• Google official announcement: Introducing Gemini 3.8 Flash
• BazaarLink Models: Gemini 3.8 Flash (unit prices and specs; query date 2026-09-04)
• Reasoning token measurements: internal to BazaarLink, 2026-09-04, 20 runs per question, same upstream endpoint
• Further reading: Gemini API TWD cost estimate 2026, How do I expense AI API costs in Taiwan? 2026 complete guide

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