Together Tev1 4B Experimental
Together AI chatTogether Tev1 4B Experimental is a Together AI chat model.It supports a 32,768-token context window.Input is priced at $0.0420/M tokens Route Together Tev1 4B Experimental via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Together Tev1 4B Experimental spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.0420/M input · $0.000000/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 Oct 22, 2026.
| Input | $0.0420/M | |
| Output | — |
Context & limits
- Context window
- 32,768 tokens
- Max input
- 32,768 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
Strengths & caveats — when to pick Together Tev1 4B Experimental
Data-driven from Together Tev1 4B Experimental's percentile within chat peers.
Where it's strong
Watch out for
- !high cost — input + output rates are in the top 100% of priced chat peers; consider a cheaper sibling for high-volume workloads
- !limited context — 32,768-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
- !strict structured output — no JSON-schema enforcement, expect retry loops
Benchmarks pending
We haven't logged public benchmark scores for Together Tev1 4B Experimental yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Together Tev1 4B Experimental 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.# Together Tev1 4B Experimental 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="together-ai/together-tev1-4b-experimental",
messages=[{"role": "user", "content": "Hello, Together Tev1 4B Experimental!"}],
)
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="together-ai/together-tev1-4b-experimental",
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 ↗Explore similar models
Together Tev1 4B Experimental doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark. Side-by-side links appear where a comparison page exists; otherwise, open the model profile.
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FAQ
How much does Together Tev1 4B Experimental cost?
Input is priced at $0.0420 per 1M tokens and output at $0.000000 per 1M tokens (Together AI, last verified Oct 22, 2026).
What is the context window of Together Tev1 4B Experimental?
Together Tev1 4B Experimental supports a 32,768-token context window.
Does Together Tev1 4B Experimental support function calling?
Together Tev1 4B Experimental 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 Together Tev1 4B Experimental good for production?
Together Tev1 4B Experimental 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 Together Tev1 4B Experimental 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 Together Tev1 4B Experimental
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.