Compatibility matrix

The platform exposes four client protocol endpoints, all reachable with the same sk-gpushare-* API key:

Protocol	Endpoint	Typical clients
OpenAI Chat	`POST /v1/chat/completions`	the OpenAI SDK and most third-party clients
Anthropic Messages	`POST /v1/messages`	the Anthropic SDK, Claude Code
OpenAI Responses	`POST /v1/responses`	the OpenAI Responses SDK, Codex CLI
Gemini Native	`POST /v1beta/models/{model}:generateContent` / `:streamGenerateContent`	Google's `genai` SDK

Not every model supports all four. The matrix is determined by channel wiring — which kind of upstream channel serves a model, and which protocols that channel declares — not by reasoning from "vendor × protocol". The table below is generated per model from the live channel table; see the legend for what each cell means.

Legend#

Symbol	Meaning
✅	Native pass-through — the client protocol matches the upstream channel's, and the gateway forwards bytes verbatim
🔄 T1 / 🔄 T2	Gateway-side translation — the gateway converts; the response carries an `X-Protocol-Translation` header (see below)
🔄 upstream	Upstream-side conversion — the gateway forwards bytes verbatim and the relay converts internally, so there is no `X-Protocol-Translation` header
—	No channel — returns 503 `no_channel_available` (note: 503, not 404)

The two kinds of 🔄 can be told apart from the response headers:

Gateway-side translation (T1 / T2 below): the gateway converts the request body into the upstream protocol and converts the response back, and the response carries an X-Protocol-Translation header.
Upstream-side conversion (marked 🔄 upstream in the table): the gateway forwards bytes verbatim and the conversion happens inside the upstream service, so there is no X-Protocol-Translation header. The protocol shape is complete for the client, but features unique to the other protocol (Anthropic's cache_control, thinking blocks) aren't guaranteed to survive semantically.

Gateway-side translation paths#

Path	Direction (client → upstream)	`X-Protocol-Translation` value	Currently exercised?
T1	OpenAI Chat → Anthropic upstream	`openai_chat_to_anthropic_messages`	✅ in production (`/v1/chat/completions` traffic on the Claude and trial pools)
T2	OpenAI Chat → Gemini upstream	`openai_chat_to_gemini_native`	✅ in production (`/v1/chat/completions` traffic on the Gemini pool)
T3	Anthropic Messages → OpenAI upstream	`anthropic_messages_to_openai_chat`	implemented, no channel combination currently triggers it
T4	Gemini Native → OpenAI upstream	`gemini_native_to_openai_chat`	implemented, no channel combination currently triggers it
T6	Gemini Native → Anthropic upstream	`anthropic_messages_to_gemini_native`	implemented, no channel combination currently triggers it

T3, T4 and T6 are reserved for future wiring: today all cross-protocol Anthropic Messages and Gemini Native traffic is absorbed by upstream-side conversion, so routing never reaches those three gateway translators.

Matrix (per model)#

The Source column uses opaque codes: x1 = in-house account pool, x2 = third-party relay, x3 = Tencent. Several codes on one model means it has several channels for failover (the column is the union over all of them).

Anthropic (11)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`claude-fable-5`	🔄 T1	✅	—	—	x2
`claude-haiku-4-5-20251001`	🔄 T1	✅	🔄 upstream	—	x1 x2
`claude-opus-4-5-thinking`	🔄 T1	✅	—	—	x2
`claude-opus-4-6`	🔄 T1	✅	🔄 upstream	—	x1 x2
`claude-opus-4-6-thinking`	✅	✅	—	—	x1 x2
`claude-opus-4-7`	🔄 T1	✅	🔄 upstream	—	x1 x2
`claude-opus-4-8`	🔄 T1	✅	🔄 upstream	—	x1 x2
`claude-opus-5`	🔄 T1	✅	—	—	x2
`claude-sonnet-4-5-20250929`	🔄 T1	✅	—	—	x2
`claude-sonnet-4-6`	🔄 T1	✅	🔄 upstream	—	x1 x2
`claude-sonnet-5`	🔄 T1	✅	🔄 upstream	—	x1 x2

OpenAI (7)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`gpt-5.5`	✅	🔄 upstream	🔄 upstream	—	x1 x2
`gpt-5.6-luna`	✅	🔄 upstream	🔄 upstream	—	x1
`gpt-5.6-sol`	✅	🔄 upstream	🔄 upstream	—	x1
`gpt-5.6-terra`	✅	🔄 upstream	🔄 upstream	—	x1
`gpt-6`	✅	🔄 upstream	🔄 upstream	—	x1
`gpt-6-astra`	✅	🔄 upstream	🔄 upstream	—	x1
`gpt-oss-120b-medium`	✅	—	—	—	x1

Google (9)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`gemini-3-flash`	✅	✅	—	✅	x1 x2
`gemini-3-flash-agent`	✅	—	—	✅	x1
`gemini-3-pro`	✅	—	—	✅	x2
`gemini-3.1-flash-lite`	✅	—	—	✅	x1
`gemini-3.1-pro-low`	✅	✅	—	✅	x1 x2
`gemini-3.5-flash-low`	✅	—	—	✅	x1 x2
`gemini-3.6-flash`	✅	—	—	✅	x1 x2
`gemini-3.7-flash`	✅	—	—	✅	x1
`gemini-pro-agent`	✅	—	—	✅	x1

xAI (10)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`grok-3-mini`	✅	—	🔄 upstream	—	x1
`grok-3-mini-fast`	✅	—	🔄 upstream	—	x1
`grok-4.20-0309-non-reasoning`	✅	—	🔄 upstream	—	x1
`grok-4.20-0309-reasoning`	✅	—	🔄 upstream	—	x1
`grok-4.20-multi-agent-0309`	✅	—	🔄 upstream	—	x1
`grok-4.3`	✅	—	🔄 upstream	—	x1
`grok-4.5`	✅	—	🔄 upstream	—	x1
`grok-4.6`	✅	—	🔄 upstream	—	x1
`grok-build-0.1`	✅	—	🔄 upstream	—	x1
`grok-composer-2.5-fast`	✅	—	🔄 upstream	—	x1

Zhipu GLM (8)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`glm-4.7`	✅	🔄 upstream	—	🔄 upstream	x2
`glm-5`	✅	🔄 upstream	—	🔄 upstream	x2 x3
`glm-5-turbo`	✅	🔄 upstream	—	🔄 upstream	x2
`glm-5.1`	✅	🔄 upstream	—	🔄 upstream	x2 x3
`glm-5.2`	✅	🔄 upstream	—	🔄 upstream	x2
`glm-5.3`	✅	—	—	—	x2
`glm-5.3-flash`	✅	—	—	—	x2
`glm-5v-turbo`	✅	—	—	—	x2

DeepSeek (6)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`deepseek-v3-0324`	✅	—	—	—	x3
`deepseek-v3.1`	✅	—	—	—	x2
`deepseek-v3.1-terminus`	✅	—	—	—	x3
`deepseek-v3.2`	✅	—	—	—	x3
`deepseek-v4-flash`	✅	—	—	—	x2 x3
`deepseek-v4-pro`	✅	—	—	—	x2 x3

ByteDance Doubao (14)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`doubao-1-5-lite-32k-250115`	✅	—	—	—	x2
`doubao-1-5-pro-32k-250115`	✅	—	—	—	x2
`doubao-seed-1-6-250615`	✅	—	—	—	x2
`doubao-seed-1-6-flash-250828`	✅	—	—	—	x2
`doubao-seed-1-6-vision`	✅	—	—	—	x2
`doubao-seed-1-8-251228`	✅	—	—	—	x2
`doubao-seed-2-0-code-preview-260215`	✅	—	—	—	x2
`doubao-seed-2-0-lite-260215`	✅	—	—	—	x2
`doubao-seed-2-0-lite-260428`	✅	—	—	—	x2
`doubao-seed-2-0-mini-260215`	✅	—	—	—	x2
`doubao-seed-2-0-mini-260428`	✅	—	—	—	x2
`doubao-seed-2-0-pro-260215`	✅	—	—	—	x2
`doubao-seed-2-1-pro-260628`	✅	—	—	—	x2
`doubao-seed-2-1-turbo-260628`	✅	—	—	—	x2

Tencent Hunyuan (4)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`hunyuan-2.0-instruct-20251111`	✅	—	—	—	x3
`hunyuan-2.0-thinking-20251109`	✅	—	—	—	x3
`hunyuan-role-latest`	✅	—	—	—	x3
`hy3`	✅	—	—	—	x2

Moonshot Kimi (4)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`kimi-k2.5`	✅	—	—	—	x2 x3
`kimi-k2.6`	✅	—	—	—	x2 x3
`kimi-k2.7-code`	✅	—	—	—	x2
`kimi-k3`	✅	—	—	—	x2

MiniMax (3)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`MiniMax-M2.5`	✅	—	—	—	x3
`MiniMax-M2.7`	✅	—	—	—	x3
`MiniMax-M3`	✅	—	—	—	x2

Alibaba Qwen (25)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`qwen-flash`	✅	—	—	—	x2
`qwen-long`	✅	—	—	—	x2
`qwen-mt-turbo`	✅	—	—	—	x2
`qwen-plus`	✅	—	—	—	x2
`qwen3-coder-plus`	✅	—	—	—	x2
`qwen3-max`	✅	—	—	—	x2
`qwen3-max-preview`	✅	—	—	—	x2
`qwen3-omni-flash`	✅	—	—	—	x2
`qwen3-vl-flash`	✅	—	—	—	x2
`qwen3-vl-plus`	✅	—	—	—	x2
`qwen3.5-122b-a10b`	✅	—	—	—	x2
`qwen3.5-27b`	✅	—	—	—	x2
`qwen3.5-35b-a3b`	✅	—	—	—	x2
`qwen3.5-397b-a17b`	✅	—	—	—	x2
`qwen3.5-flash`	✅	—	—	—	x2
`qwen3.5-plus`	✅	—	—	—	x2
`qwen3.6-27b`	✅	—	—	—	x2
`qwen3.6-35b-a3b`	✅	—	—	—	x2
`qwen3.6-flash`	✅	—	—	—	x2
`qwen3.6-max-preview`	✅	—	—	—	x2
`qwen3.6-plus`	✅	—	—	—	x2
`qwen3.7-flash`	✅	—	—	—	x2
`qwen3.7-max`	✅	—	—	—	x2
`qwen3.7-plus`	✅	—	—	—	x2
`qwen3.8-27b`	✅	—	—	—	x2
`qwen3.8-max`	✅	—	—	—	x2

Xiaomi MiMo (1)#

Model	OpenAI Chat	Anthropic Messages	OpenAI Responses	Gemini Native	Source
`mimo-v2.5-pro`	✅	—	—	—	x2

Image / video / music / voice SKUs use their own endpoint families and are outside this 4-protocol matrix — see Image / video APIs and Full model list.

Side effects of a translated path#

On a gateway-side translation (T1 / T2) the response carries diagnostic headers:

X-Protocol-Translation: openai_chat_to_anthropic_messages
X-Protocol-Warning: response_format=json_object dropped (Anthropic has no equivalent); n=2 dropped (Anthropic returns one completion)

The X-Protocol-Translation value is {client protocol}_to_{upstream protocol} (see the table above).
X-Protocol-Warning is generated from the fields actually dropped on this request, joined with ; . The header is absent when nothing was dropped. Common drops:
- OpenAI Chat → Anthropic (T1): response_format, n, tools.image_generation and other fields Anthropic has no concept of
- Anthropic → OpenAI (T3, reserved): cache_control markers
- Gemini → Anthropic (T6, reserved): safetySettings / cachedContent / codeExecution

If your request depends heavily on those fields, pick a protocol endpoint that carries them natively (the ✅ columns). Upstream-side conversion (the "upstream conversion" cells) carries neither header — the gateway only sees a byte stream, and what gets dropped is up to the upstream.

Checking a combination yourself#

# send a request with your key and look at the HTTP status and response headers
curl -i https://zhonkezhonkeapi.dflop.top/v1/chat/completions \
  -H "Authorization: Bearer sk-gpushare-xxx" \
  -H "Content-Type: application/json" \
  -d '{"model":"<model-id>","messages":[{"role":"user","content":"hi"}]}'

200 — the combination works. An X-Protocol-Translation header means a gateway-side translation path; its absence means native pass-through or upstream-side conversion.
400 model_not_found — the model id isn't in the registry at all (typo, or retired). Identical on every protocol, with a message like model `xxx` is not available.
503 no_channel_available — the model exists but has no channel on the protocol you used. Try an endpoint marked ✅ or 🔄 in the matrix (/v1/messages, /v1/responses or /v1beta/models/{id}:generateContent).

If a — cell returns 200 in practice, trust the response — channel wiring changes ahead of the docs. Note that the three protocols return differently shaped error bodies (each follows its own official schema) — see Error codes.

How current is this?#

The tables on this page are generated from the live channel table (last generated 2026-08-18); they need regenerating whenever channel wiring changes. For the latest model list:

Public catalog: GET /api/v1/models/public (no auth; includes callable=false placeholder SKUs and non-chat SKUs, so filter on callable and endpoint_type when consuming it from a script)
Model plaza: zhonkemodel.dflop.top/models