Jetbrains Mellum2 12B A2 5B Instruct
W&B Inference chat Deprecated 30d agomodel fallback routing to swap models without code changes.
Jetbrains Mellum2 12B A2 5B Instruct is a W&B Inference chat model.It supports a 131,000-token context window.Input is priced at $0.0500/M tokens and output at $0.1000/M tokens. Route Jetbrains Mellum2 12B A2 5B Instruct via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
Estimate Jetbrains Mellum2 12B A2 5B Instruct spend
Pick a workload, fine-tune the sliders, and see the monthly bill.
Estimate uses $0.0500/M input · $0.1000/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 | $0.0500/M | |
| Output | $0.1000/M | |
| Blended (3:1 in:out) | $0.0625/M Cross-model comparable price |
Context & limits
- Context window
- 131,000 tokens
- Max input
- 131,000 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 Jetbrains Mellum2 12B A2 5B Instruct
Data-driven from Jetbrains Mellum2 12B A2 5B Instruct's percentile within chat peers.
Where it's strong
Watch out for
- !high cost — input + output rates are in the top 98% of priced chat peers; consider a cheaper sibling for high-volume workloads
- !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
- !already deprecated — provider stopped accepting new traffic 30 days ago
Benchmarks pending
We haven't logged public benchmark scores for Jetbrains Mellum2 12B A2 5B Instruct yet. Have one to contribute? Submit a source — citations help us prioritise.
Call Jetbrains Mellum2 12B A2 5B Instruct 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.# Jetbrains Mellum2 12B A2 5B Instruct 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="wandb-inference/jetbrains-mellum2-12b-a2-5b-instruct",
messages=[{"role": "user", "content": "Hello, Jetbrains Mellum2 12B A2 5B Instruct!"}],
)
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="wandb-inference/jetbrains-mellum2-12b-a2-5b-instruct",
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
Jetbrains Mellum2 12B A2 5B Instruct 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 Jetbrains Mellum2 12B A2 5B Instruct cost?
Input is priced at $0.0500 per 1M tokens and output at $0.1000 per 1M tokens (W&B Inference, last verified Oct 22, 2026).
What is the context window of Jetbrains Mellum2 12B A2 5B Instruct?
Jetbrains Mellum2 12B A2 5B Instruct supports a 131,000-token context window.
Does Jetbrains Mellum2 12B A2 5B Instruct support function calling?
Jetbrains Mellum2 12B A2 5B Instruct 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 Jetbrains Mellum2 12B A2 5B Instruct good for production?
Jetbrains Mellum2 12B A2 5B Instruct 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 Jetbrains Mellum2 12B A2 5B Instruct 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 Jetbrains Mellum2 12B A2 5B Instruct
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.