Qwen 2.5 7B Instruct

qwen/qwen-2.5-7b-instruct

Qwen (Alibaba)· 33K ctx

API onlytool callstructured quant: unknown

spread (output, p90 ÷ p10)

— too few providers

$0.0500 – $0.300 · 3 providers · max÷min 6.0×

3 providers priced · 5 offerings

Including routers & resellers

Cheapest / median / spread use providers that serve the model on their own capacity: first-party lab, hyperscaler, inference host.

Provider classes in the stats:

Blended $/M assumptionsInput : output: 1Cache-hit share of input%

blended = 90.9% input × [(1 − 70% cache) × input + 70% cache × cache-read] + 9.1% × output + cache writes (30% of uncached input) where a write price is published

A provider that publishes no cache price is blended with cache share 0 (all input at the input price) and labelled “no cache price published” — never penalised against identical in/out prices.

Provider	Input	Output	Cache rd	Blended
SiliconFlow (China)CN inference host	$0.0500	$0.0500	—	$0.0500no cache price published
Alibaba (China)CNfirst-party first-party lab	$0.0720	$0.144	—	$0.0785no cache price published
OpenRouter router / aggregator	$0.100	$0.200	—	$0.109no cache price published
Kilo Gateway router / aggregator	$0.100	$0.200	—	$0.109no cache price published
Together AI inference host	$0.300	$0.300	—	$0.300no cache price published

Connect

Provider (default: cheapest output among direct providers)

$0.0500 /M · inference host

opencode.json

{
  "provider": {
    "siliconflow-cn": {
      "npm": "@ai-sdk/openai-compatible",
      "options": {
        "baseURL": "https://api.siliconflow.cn/v1"
      },
      "models": {
        "Qwen/Qwen2.5-7B-Instruct": {}
      }
    }
  }
}

Set SILICONFLOW_CN_API_KEY in your environment. Generated — verify against the OpenCode docs.

Not enough history yet — the min/median/max sparkline fills in as the daily snapshot accumulates.

Data: models.dev (MIT), snapshot 2026-10-19. Prices are vendor-published; verify before purchase. Methodology.