Gemini 1.5 Flash 8B
Google AI chat Deprecated 401d agomodel fallback routing to swap models without code changes.
Gemini 1.5 Flash 8B is a Google AI chat model.It supports a 1,048,576-token context windowwith up to 8,192 output tokens. Capabilities include function calling, vision, prompt caching. Route Gemini 1.5 Flash 8B via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
We don't have verified per-token pricing for Gemini 1.5 Flash 8B yet. If you have a source from Google AI's documentation, help us add it — your submission gets reviewed within 48 hours.
Pricing
Per-token rates, expressed in USD per 1M tokens. Verified May 7, 2026.
| Input | — | |
| Output | — |
Context & limits
- Context window
- 1,048,576 tokens
- Max input
- 1,048,576 tokens
- Max output
- 8,192 tokens
- Modalities
- vision, text
Capabilities
- Function calling ✓ supported
- Parallel tool calls — not advertised
- Vision input ✓ supported
- Audio input — not advertised
- Audio output — not advertised
- PDF input — not advertised
- Streaming ✓ supported
- Structured output ✓ supported
- Prompt caching ✓ supported
- Reasoning — not advertised
Strengths & caveats — when to pick Gemini 1.5 Flash 8B
Data-driven from Gemini 1.5 Flash 8B's percentile within chat peers.
Where it's strong
- +long-context tasks — context window in the top 2% of peers
Watch out for
- !already deprecated — provider stopped accepting new traffic 401 days ago
Benchmark scores
Reported public benchmark numbers. Each row links to the source. Faded bar shows 6-peer average for context.
Call Gemini 1.5 Flash 8B via Agent Command Center
One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.
agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.# Gemini 1.5 Flash 8B via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC
client = AgentCC(
api_key=os.environ["AGENTCC_API_KEY"], # from app.futureagi.com → Settings → API Keys
base_url="https://gateway.futureagi.com/v1",
)
resp = client.chat.completions.create(
model="google/gemini-1-5-flash-8b",
messages=[{"role": "user", "content": "Hello, Gemini 1.5 Flash 8B!"}],
)
print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")
# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
model="google/gemini-1-5-flash-8b",
messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost: ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache: ", raw.headers.get("x-agentcc-cache"))AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗Advanced: fallback + cache config (YAML) ▸
strategy: cost-optimized
targets:
- model: gemini-1-5-flash-8b
provider: google
weight: 80
fallbacks:
- model: gpt-4o-mini
provider: azure-openai
- model: gpt-4o-mini-2024-07-18
provider: azure-openai
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true } Explore similar models
Grouped by Chatbot Arena tier (Gemini 1.5 Flash 8B sits at 1259 ELO). Side-by-side links appear where a comparison page exists; otherwise, open the model profile.
- Gemini 3.1 Pro previewGoogle AI · $2.00/M in · $12.00/M out · 1,048,576 ctxView model →
- Gemini 3 Pro PreviewGoogle AI · $2.00/M in · $12.00/M out · 1,048,576 ctxView model →
- Gemini 2.5 ProGoogle AI · $1.25/M in · $10.00/M out · 1,048,576 ctxView model →
- Gemini 3 Flash previewGoogle AI · $0.500/M in · $3.00/M out · 1,048,576 ctxView model →
- GPT-4o miniAzure OpenAI · $0.150/M in · $0.600/M out · 128,000 ctxView model →
- GPT-4o mini (2024-07-18)Azure OpenAI · $0.150/M in · $0.600/M out · 128,000 ctxView model →
- Gemini 1.5 FlashGoogle Vertex AI · $0.0750/M in · $0.300/M out · 1,000,000 ctxView model →
- Mistral Large latestMistral AI · $0.500/M in · $1.50/M out · 262,144 ctxView model →
≥30 ELO higher
- Gemini 4 ArgonGoogle AI · $2.00/M in · $10.00/M out · 1,048,576 ctxView model →
- Claude Opus 5.5Azure AI Foundry · $4.00/M in · $20.00/M out · 1,000,000 ctxView model →
- Claude Fable 5Azure AI Foundry · $10.00/M in · $50.00/M out · 1,000,000 ctxView model →
- Claude Fable 5.1Azure AI Foundry · $10.00/M in · $50.00/M out · 1,000,000 ctxView model →
FAQ
How much does Gemini 1.5 Flash 8B cost?
Public per-token pricing for Gemini 1.5 Flash 8B is not yet published. Submit a source on this page to help us add it.
What is the context window of Gemini 1.5 Flash 8B?
Gemini 1.5 Flash 8B supports a 1,048,576-token context window with up to 8,192 output tokens.
Does Gemini 1.5 Flash 8B support function calling?
Yes — Gemini 1.5 Flash 8B supports function (tool) calling.
Is Gemini 1.5 Flash 8B good for production?
Gemini 1.5 Flash 8B is well-suited for long-context tasks — context window in the top 2% of peers. Consider alternatives if you need already deprecated — provider stopped accepting new traffic 401 days ago.
How can I route to Gemini 1.5 Flash 8B with fallback?
Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.
Useful links for Gemini 1.5 Flash 8B
Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.
Third-party evals — verify the marketing.
Cross-check our number against the rest of the ecosystem.