GPT 3.5 Turbo 0613
OpenAI chatGPT 3.5 Turbo 0613 is an OpenAI chat model.It supports a 4,097-token context windowwith up to 4,096 output tokens.Input is priced at $1.50/M tokens and output at $2.00/M tokens. Capabilities include function calling, prompt caching. Route GPT 3.5 Turbo 0613 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate GPT 3.5 Turbo 0613 spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $1.50/M input · $2.00/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 | $1.50/M | |
| Output | $2.00/M |
Limits
- Context window
- 4,097 tokens
- Max input
- 4,097 tokens
- Max output
- 4,096 tokens
- Modalities
- text
Capabilities
- Function calling ✓ supported
- 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 ✓ supported
- Reasoning — not advertised
Where it's strong
- +prompt caching — only 23% of chat models on Future AGI advertise this
Watch out for
- !limited context — 4,097-token window is in the bottom quartile; not ideal for long documents or large RAG
- !small context (under 16K tokens)
- !strict structured output — no JSON-schema enforcement, expect retry loops
Benchmark scores
Reported public benchmark numbers. Each row links to the source.
Call GPT 3.5 Turbo 0613 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.# GPT 3.5 Turbo 0613 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="openai/gpt-3-5-turbo-0613",
messages=[{"role": "user", "content": "Hello, GPT 3.5 Turbo 0613!"}],
)
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="openai/gpt-3-5-turbo-0613",
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 ↗Same model on other providers
gpt-3-5-turbo-0613 is also available via 1 other route. Pricing, regions, and capabilities can differ — compare before routing production traffic.
| Provider | Input / 1M | Output / 1M | Verified |
|---|---|---|---|
| GitHub Copilot | — | — | May 12, 2026 |
Compare with similar models
GPT 3.5 Turbo 0613 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 GPT 3.5 Turbo 0613 cost?
Input is priced at $1.50 per 1M tokens and output at $2.00 per 1M tokens (OpenAI, last verified May 7, 2026).
What is the context window of GPT 3.5 Turbo 0613?
GPT 3.5 Turbo 0613 supports a 4,097-token context window with up to 4,096 output tokens.
Does GPT 3.5 Turbo 0613 support function calling?
Yes — GPT 3.5 Turbo 0613 supports function (tool) calling.
Is GPT 3.5 Turbo 0613 good for production?
GPT 3.5 Turbo 0613 is well-suited for prompt caching — only 23% of chat models on Future AGI advertise this. Consider alternatives if you need limited context — 4,097-token window is in the bottom quartile; not ideal for long documents or large RAG.
How can I route to GPT 3.5 Turbo 0613 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 GPT 3.5 Turbo 0613
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.