USE CASES // OPEN SOURCE INFERENCE

Open weights closed the quality gap. Hoonify closed the price gap.

Llama, Qwen, and DeepSeek match GPT-4o and Claude on the benchmarks that matter for RAG, agents, code assistants, and classification. But for 10-40x lower cost. Here's what to switch.

COST

Same volume. Different bills.

100 million tokens / month, 55/45 input/output.

That's a busy chatbot, a small RAG pipeline, or one decent code assistant. Frontier model providers price this between $1,200–$1,750/mo. Hoonify-hosted open weights handle the same volume for under $40.

Best Hoonify model vs. priciest frontier
99% cheaper
$1,175$9 / month
Model$/1M IN$/1M OUT@ 100M tok/mo
GPT-4oFrontier
$5.00$20.00$1,175
Claude 3.5 SonnetFrontier
$3.00$15.00$840
Llama 3.3 70BHoonify
General-purpose default
$0.18$0.54$34
DeepSeek V3Hoonify
Top quality at our top tier
$0.45$1.10$74
Qwen 2.5 72BHoonify
Multilingual, strong at code + math
$0.20$0.58$37
Llama 3.1 8BHoonify
Cheapest fast option
$0.06$0.12$9cheapest

QUALITY

Within a percentage point on the benchmarks people actually run.

On the standard reasoning, math, and coding benchmarks, the gap between frontier and open is tighter than the cost gap suggests. On instruction following (IFEval), Llama 3.3 70B actually leads.

Numbers are directional. Source: model release cards + open leaderboards.

BenchmarkGPT-4oClaude 3.5 SonnetLlama 3.3 70BDeepSeek V3
MMLU88.788.386.088.5
HumanEval90.292.088.489.0
GSM8K96.096.495.196.5
MATH76.678.370.075.5
IFEval84.088.792.188.0

USE CASES

Where the math is obvious.

Four common workloads where customers switch and don't look back. Pick the one closest to yours and we'll seed the workbench with the right model.

Document Q&A / RAG

Llama 3.3 70B handles the long tail at GPT-4o quality.

Most RAG queries don't need frontier reasoning — they need fast, accurate retrieval-grounded answers. Llama 3.3 70B keeps quality on par with GPT-4o for everyday extraction, summarization, and grounded answering.

Model
Llama 3.3 70B
At
80M tok/mo
Save vs GPT-4o
~97%
$940$27 / moTry in workbench

Code assistant / copilot

DeepSeek V3 and Qwen 2.5 are competitive on HumanEval and SWE-bench.

Code-shaped tasks are exactly where open-weight models have caught up fastest. DeepSeek V3 outperforms GPT-4o on HumanEval-Plus and matches it on SWE-bench Lite at a fraction of the cost.

Model
DeepSeek V3
At
40M tok/mo
Save vs GPT-4o
~94%
$470$30 / moTry in workbench

Customer support agents

Predictable spend per ticket. EU pool by default for GDPR.

Agents are cost-sensitive — every escalation is multiple model calls. Hoonify's per-token rate is constant, no surge pricing. Pin the EU pool to keep customer data in-region.

Model
Llama 3.3 70B
At
200M tok/mo
Save vs GPT-4o
~97%
$2,350$68 / moTry in workbench

Bulk classification / extraction

Llama 3.1 8B at $0.06/1M input tokens.

Tagging, sentiment, intent classification, structured extraction — small models nail this with negligible quality loss vs. frontier. Run millions of rows for the price of a single GPT-4o pass.

Model
Llama 3.1 8B
At
1000M tok/mo
Save vs GPT-4o
~99%
$11,750$87 / moTry in workbench

DECISION

When to switch. When not to.

We'll tell you both. Open source isn't a religion — it's a tool that saves you 10–40× on the workloads it's suited for.

Switch when…

  • Cost per inference matters at all (most workloads above 1M tokens/mo).
  • You need data residency — pin a Hoonify pool, no logs to OpenAI / Anthropic.
  • You want predictable rate limits without contract-only escalations.
  • You'd benefit from quantized variants (FP8, INT4) for higher TTFT or throughput.
  • You want to fine-tune (LoRA, full FT) without leaving the API surface.

Stay frontier when…

  • You need the latest reasoning model the day it ships (GPT-4.x / Claude Opus tier).
  • Multimodal vision quality is your primary requirement (still a frontier lead).
  • Total volume is small enough that the price difference is rounding error.
  • Your team has zero appetite for any provider migration work.

GET STARTED

Try it before you switch.

$5 in free credits. No card required.

Run real prompts against the same models you'd use in production. If quality holds for your workload, the rest is migration.

  • 10–40× cheaper per token vs frontier
  • No log retention. Pin a pool for residency.
  • OpenAI-compatible API — swap one line.
  • Predictable rate limits, no contract-only tiers.