QuickSilver Pro vs OpenAI
For workloads where an open-source model is quality-equivalent, QuickSilver Pro is up to 30× lower than OpenAI. DeepSeek V4 Flash replaces GPT-4o-mini at ~71% lower cost; V4 Pro replaces o3-mini at ~6x lower output cost. For audio and the Assistants API — stay on OpenAI. Vision we do have: 37 of our 71 models accept image input. This page is honest about which parts of OpenAI are worth their premium and which aren't.
At a glance
| Feature | QuickSilver Pro | openai |
|---|---|---|
| Catalog | GPT-6.1 Sol, GPT-6 Luna, Claude Opus 5.5, Claude Sonnet 5.5, Claude Haiku 5.5, Gemini 3.8 Flash, Mistral Large 4, DeepSeek V4.1 Flash, Qwen3.8 Max, Kimi K3, GLM 5.3 and Grok 4.7 | GPT-4, o1/o3-mini, DALL-E, Whisper, TTS |
| Model weights | Open (MIT / Apache) | Closed |
| Low-cost chat cost (GPT-4o-mini / DeepSeek V4 Flash) | $0.086 / $0.173 | $0.15 / $0.60 |
| Premium reasoning cost (o3-mini / DeepSeek V4 Pro) | $0.70 / $2.10 | $1.10 / $4.40 |
| Vision (image input) | 37 of 71 models | Yes (GPT-4o) |
| Audio (Whisper / TTS) | No | Yes |
| Image generation | Gemini 3 Pro Image, FLUX.2 Pro, FLUX.1 Schnell, SDXL Turbo, FLUX.2 Klein, Qwen-Image Max, Seedream 5.0 Pro, Seedream 4, Bria FIBO 1.5 and GPT Image 2 | Yes (DALL-E) |
| Assistants API + built-in tools | No | Yes |
| OpenAI-compatible chat + tools + JSON | Yes — json_schema varies by model | Yes (original) |
| Minimum top-up | $5 | $5 |
Pricing (per million tokens, USD)
Competitor list prices as published by each provider.
| Model | QSP input | QSP output | openai input | openai output | vs. list |
|---|---|---|---|---|---|
| deepseek-v4-flash vs gpt-4o-mini | $0.086 | $0.173 | $0.15 | $0.60 | ~71% |
| deepseek-v4-pro vs o3-mini | $0.70 | $2.10 | $1.10 | $4.40 | ~52% output |
| qwen3.6-35b vs gpt-4o | $0.112 | $0.80 | $2.50 | $10.00 | ~92% |
| kimi-k2.6 | $0.5472 | $2.728 | — | — | specialist tier |
Migration - two lines
from openai import OpenAI
client = OpenAI(
base_url="https://api.quicksilverpro.io/v1",
api_key=os.environ["QSP_KEY"],
)
r = client.chat.completions.create(
model="deepseek-v4-pro",
messages=[{"role": "user", "content": "Hi"}],
)FAQ
DeepSeek V4 Flash vs GPT-4o-mini: ~43% on input, ~71% on output. DeepSeek V4 Pro vs o3-mini: ~1.6x on input, ~2x on output. Same underlying task quality on most text-only benchmarks.
DeepSeek V4 Pro maps cleanly to o3-mini for premium reasoning workloads with long context (1M tokens vs o3-mini’s 200K), at $0.70 / $2.10 vs $1.10/$4.40 — about 2× lower on output. Kimi K2.6 is in an Opus-class agentic / planning niche where OpenAI doesn’t have a clean analog — if your evals are picking Claude Opus, K2.6 at $0.5472 / $2.728 is the open-source comparable.
Yes, unchanged. Only the base_url + api_key + model change. Streaming, tool calling, usage accounting — all supported. json_schema strict mode is model-dependent: the Claude models do not support it, so a schema there is advisory and the enforced path is a tool with `strict: true`. V4-wave models (V4 Flash, V4 Pro, Kimi K2.6) think by default; pass `reasoning: { enabled: false }` for non-thinking chat.
Whisper / TTS, the Assistants API, embeddings, and any task where GPT-4 measurably beats DeepSeek V4 on your evals. Vision and image generation are not reasons to stay: 37 of our 71 models take image input, and Gemini 3 Pro Image, FLUX.2 Pro, FLUX.1 Schnell, SDXL Turbo, FLUX.2 Klein, Qwen-Image Max, Seedream 5.0 Pro, Seedream 4, Bria FIBO 1.5 and GPT Image 2 generate images.
Yes — run two OpenAI SDK instances, one per provider, and route per-request by task. Many teams do exactly this: OpenAI for audio and Assistants, QSP for chat, vision and image generation. The hybrid bill is typically 10-30% of the all-OpenAI bill.