GPT 3.5 Turbo Instruct 0914
Azure OpenAI completionGPT 3.5 Turbo Instruct 0914 is an Azure OpenAI text completion model.It supports a 4,097-token context window.Input is priced at $1.50/M tokens and output at $2.00/M tokens. Route GPT 3.5 Turbo Instruct 0914 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate GPT 3.5 Turbo Instruct 0914 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 12, 2026.
| Input | $1.50/M | |
| Output | $2.00/M |
Limits
- Context window
- 4,097 tokens
- Max input
- 4,097 tokens
- Max output
- —
- 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
- !small context (under 16K tokens)
Benchmarks pending
We haven't logged public benchmark scores for GPT 3.5 Turbo Instruct 0914 yet. Have one to contribute? Submit a source — citations help us prioritise.
Call GPT 3.5 Turbo Instruct 0914 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 Instruct 0914 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="azure-openai/gpt-3-5-turbo-instruct-0914",
messages=[{"role": "user", "content": "Hello, GPT 3.5 Turbo Instruct 0914!"}],
)
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="azure-openai/gpt-3-5-turbo-instruct-0914",
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-instruct-0914 is also available via 1 other route. Pricing, regions, and capabilities can differ — compare before routing production traffic.
| Provider | Input / 1M | Output / 1M | Verified |
|---|---|---|---|
| OpenAI | $1.50/M | $2.00/M | May 12, 2026 |
Compare with similar models
GPT 3.5 Turbo Instruct 0914 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 Instruct 0914 cost?
Input is priced at $1.50 per 1M tokens and output at $2.00 per 1M tokens (Azure OpenAI, last verified May 12, 2026).
What is the context window of GPT 3.5 Turbo Instruct 0914?
GPT 3.5 Turbo Instruct 0914 supports a 4,097-token context window.
Does GPT 3.5 Turbo Instruct 0914 support function calling?
GPT 3.5 Turbo Instruct 0914 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 GPT 3.5 Turbo Instruct 0914 good for production?
GPT 3.5 Turbo Instruct 0914 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 GPT 3.5 Turbo Instruct 0914 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 Instruct 0914
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.