[Inception](/ai-gateway/models/labs/inception) # Mercury Coder Small Beta Mercury Coder Small Beta is Inception's compact diffusion coding model. Mercury Coder Small Beta scores 90.0 on HumanEval and 84.8 on fill-in-the-middle (FIM). Your use is subject to Inception's [Terms](https://www.inceptionlabs.ai/terms) & [Privacy](https://www.inceptionlabs.ai/terms) Policies. Tool Use [Use with AI Gateway](https://vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai%3Futm_source%3Dgateway-model-page%26utm_campaign%3Dai-gateway-models&title=Get+Started+with+Vercel+AI+Gateway) [View docs](https://vercel.com/docs/ai-gateway) AI SDKChat CompletionsMessagesResponses ``` 1import { streamText } from 'ai' 2 3const result = streamText({ 4 model: 'inception/mercury-coder-small', 5 prompt: 'Why is the sky blue?' 6}) ``` [Read docs](https://vercel.com/docs/ai-gateway/sdks-and-apis/ai-sdk) [Overview](/ai-gateway/models/mercury-coder-small) [API](/ai-gateway/models/mercury-coder-small/api) [About](/ai-gateway/models/mercury-coder-small/about) [Providers](/ai-gateway/models/mercury-coder-small/providers) [Latency](/ai-gateway/models/mercury-coder-small/latency) [Uptime](/ai-gateway/models/mercury-coder-small/uptime) [Status](/ai-gateway/models/mercury-coder-small/status) [Similar](/ai-gateway/models/mercury-coder-small/similar) [FAQ](/ai-gateway/models/mercury-coder-small/faq) ## [Copy link to heading](#playground)Playground Try out Mercury Coder Small Beta by Inception. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days. ![inception logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Finception.png&w=48&q=75)Mercury Coder Small Beta ![inception logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Finception.png&w=96&q=75) Mercury Coder Small Beta ## [Copy link to heading](#providers)Providers Route requests across multiple providers. Copy a provider slug to set your preference. Visit the [docs](/docs/ai-gateway/provider-options) for more info. Using a provider means you agree to their terms, listed under Legal. | Provider | | --- | | Context | Max Output | Latency | Throughput | Input | Output | Cache | Web Search | Capabilities | ZDR | No Training | Free Tier | Release Date | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | ![inception logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Finception.png&w=48&q=75) [Inception](/ai-gateway/models/providers/inception) Legal:[Terms](https://www.inceptionlabs.ai/terms)•[Privacy](https://www.inceptionlabs.ai/terms) | 32K | 16K | 0.5s | | $0.25/M | $1/M | | — | | | | | 02/26/2025 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ## [Copy link to heading](#throughput)Throughput24 hours 1W 1D P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/metrics) for more info. ## [Copy link to heading](#latency)Latency24 hours 1W 1D P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/metrics) for more info. ## [Copy link to heading](#uptime)Uptime24 hours 1W 1D 1H Direct request success rate on AI Gateway and per-provider. Visit the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/uptime) for more info. 1W 1D 1H ## [Copy link to heading](#more-models-by-inception)More models by Inception All Text Code | Model | | --- | | Context | Latency | Throughput | Input | Output | Cache | Web Search | Capabilities | Providers | ZDR | No Training | Free Tier | Release Date | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | ![inception logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Finception.png&w=48&q=75) [inception/mercury-2](/ai-gateway/models/mercury-2) | 128K | 0.4s | | $0.25/M | $0.75/M | Read:$0.03/M Write:— | — | | ![inception logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Finception.png&w=48&q=75) | | | | 02/24/2026 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ## [Copy link to heading](#about-mercury-coder-small-beta)About Mercury Coder Small Beta Mercury Coder Small Beta belongs to the Mercury family of diffusion large language models (dLLMs) from Inception Labs. Unlike transformer-based code models that emit tokens one at a time, Mercury Coder Small Beta uses a coarse-to-fine generation process. It produces a rough complete draft and refines all positions in parallel over a small number of passes. Mercury Coder Small Beta runs faster than autoregressive alternatives at comparable quality tiers. Live metrics on this page show current rates. Mercury Coder Small Beta scores 90.0 on HumanEval and 84.8 on fill-in-the-middle (FIM) tasks. FIM maps directly to IDE autocomplete, where the model completes code surrounded by existing context on both sides. Its MBPP score of 76.6 and MultiPL-E score of 76.2 reflect results across Python-centric and multi-language coding evaluations. The model targets high-frequency, latency-sensitive coding applications: inline completions, documentation generation triggered on keystrokes, and fast unit test synthesis. At $0.25 input / $1.0 output per million tokens, Mercury Coder Small Beta suits developers who need reliable code quality without the cost or latency overhead of frontier-scale models on every request. ## [Copy link to heading](#what-to-consider-when-choosing-a-provider)What To Consider When Choosing a Provider - Configuration: Mercury Coder Small Beta's diffusion generation pattern differs from autoregressive streaming. Factor that in when you design editor integrations or autocomplete pipelines that depend on incremental token delivery. - Zero Data Retention: Zero Data Retention is offered on a per-provider and model basis. See the [documentation](https://vercel.com/docs/ai-gateway/security-and-compliance/zdr) for details. - Authentication: AI Gateway authenticates requests using an [API key](https://vercel.com/docs/ai-gateway/authentication-and-byok#api-key-authentication) or [OIDC token](https://vercel.com/docs/ai-gateway/authentication-and-byok#oidc-token-authentication). You do not need to manage provider credentials directly. ## [Copy link to heading](#when-to-use-mercury-coder-small-beta)When to Use Mercury Coder Small Beta ### Best for - IDE inline autocomplete: Low response latency for keystroke-level completions - Fill-in-the-middle completions: Editor completions surrounded by existing code context on both sides - High-volume coding pipelines: Per-call cost is a significant factor at scale - CI/CD test generation: Fast unit test and docstring generation triggered inside pipelines - Lightweight agent loops: Coding agents that make many small inference calls per task ### Consider alternatives when - Deep multi-file reasoning: Tasks span very large codebases and demand cross-file analysis - Competitive programming benchmarks: LiveCodeBench-style problems are the primary use case - Broad domain knowledge: Workload includes long-form prose or complex math proofs beyond code - Maximum context window: Context length is the binding constraint for the task ## [Copy link to heading](#conclusion)Conclusion Mercury Coder Small Beta brings diffusion-based code generation to contexts where speed and throughput matter most. Its FIM score is 84.8 and HumanEval is 90.0 in Inception's published benchmarks, so it fits teams balancing quality against cost and latency in IDE experiences and high-frequency agent loops.