Baai Bge Reranker V2 M3

Novita AI rerank

Baai Bge Reranker V2 M3 is a Novita AI rerank model.It supports a 8,000-token context windowwith up to 8,000 output tokens.Input is priced at $0.0100/M tokens and output at $0.0100/M tokens. Route Baai Bge Reranker V2 M3 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 12, 2026 View source ↗
Cost calculator

Estimate Baai Bge Reranker V2 M3 spend

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

~3K in / ~400 out · 5K req/day
3,000
08,000
400
08,000
5,000
01,000,000
Per request
$0.000034
in $0.000030 · out $0.000004
Per day
$0.1700
5,000 requests
Per month
$5.17
152,188 requests

Estimate uses $0.0100/M input · $0.0100/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 $0.0100/M
Output $0.0100/M

Limits

Context window
8,000 tokens
Max input
8,000 tokens
Max output
8,000 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

  • !small context (under 16K tokens)

Benchmarks pending

We haven't logged public benchmark scores for Baai Bge Reranker V2 M3 yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Baai Bge Reranker V2 M3 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.
# Baai Bge Reranker V2 M3 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="novita-ai/baai-bge-reranker-v2-m3",
    messages=[{"role": "user", "content": "Hello, Baai Bge Reranker V2 M3!"}],
)

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="novita-ai/baai-bge-reranker-v2-m3",
    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 ↗

Compare with similar models

Baai Bge Reranker V2 M3 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 Baai Bge Reranker V2 M3 cost?

Input is priced at $0.0100 per 1M tokens and output at $0.0100 per 1M tokens (Novita AI, last verified May 12, 2026).

What is the context window of Baai Bge Reranker V2 M3?

Baai Bge Reranker V2 M3 supports a 8,000-token context window with up to 8,000 output tokens.

Does Baai Bge Reranker V2 M3 support function calling?

Baai Bge Reranker V2 M3 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 Baai Bge Reranker V2 M3 good for production?

Baai Bge Reranker V2 M3 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 Baai Bge Reranker V2 M3 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 Baai Bge Reranker V2 M3

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