Chat Bison 001

Google Vertex AI chat

Chat Bison 001 is a Google Vertex AI chat model.It supports a 8,192-token context windowwith up to 4,096 output tokens.Input is priced at $0.125/M tokens and output at $0.125/M tokens. Route Chat Bison 001 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: May 7, 2026 View source ↗
Cost calculator

Estimate Chat Bison 001 spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
08,192
400
04,096
5,000
01,000,000
Per request
$0.000425
in $0.000375 · out $0.000050
Per day
$2.13
5,000 requests
Per month
$64.68
152,188 requests

Estimate uses $0.1250/M input · $0.1250/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified May 7, 2026.

Input $0.125/M
Output $0.125/M

Limits

Context window
8,192 tokens
Max input
8,192 tokens
Max output
4,096 tokens
Modalities
text

Capabilities

  • Function calling — not advertised
  • Parallel tool calls — not advertised
  • Vision input — not advertised
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input — not advertised
  • Streaming ✓ supported
  • Structured output — not advertised
  • Prompt caching — not advertised
  • Reasoning — not advertised

Where it's strong

Watch out for

  • !high cost — input + output rates are in the top 91% of priced chat peers; consider a cheaper sibling for high-volume workloads
  • !limited context — 8,192-token window is in the bottom quartile; not ideal for long documents or large RAG
  • !agentic workflows — no advertised function-calling; use a tool-capable model and route via Agent Command Center for fallback
  • !small context (under 16K tokens)
  • !strict structured output — no JSON-schema enforcement, expect retry loops

Benchmarks pending

We haven't logged public benchmark scores for Chat Bison 001 yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Chat Bison 001 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.

SDK
Native Future AGI client (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.
# Chat Bison 001 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="vertex-ai/chat-bison-001",
    messages=[{"role": "user", "content": "Hello, Chat Bison 001!"}],
)

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="vertex-ai/chat-bison-001",
    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"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗

Same model on other providers

chat-bison-001 is also available via 1 other route. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
Google AI$0.125/M$0.125/MMay 12, 2026

Compare with similar models

Chat Bison 001 doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark.

FAQ

How much does Chat Bison 001 cost?

Input is priced at $0.125 per 1M tokens and output at $0.125 per 1M tokens (Google Vertex AI, last verified May 7, 2026).

What is the context window of Chat Bison 001?

Chat Bison 001 supports a 8,192-token context window with up to 4,096 output tokens.

Does Chat Bison 001 support function calling?

Chat Bison 001 does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.

Is Chat Bison 001 good for production?

Chat Bison 001 is best evaluated against your own production traces. Pipe traffic through Agent Command Center to compare it head-to-head against alternatives in shadow mode.

How can I route to Chat Bison 001 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 Chat Bison 001

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.