The closest comparison on this site: both are AI gateways written in Go, both run as a single binary, both are fast. The differences are in the tail latency, the memory it takes to get there, and which features sit behind an enterprise license. Measured, with the harness published.
Bifrost is the gateway Maxim AI builds alongside its evaluation and observability platform. It is a serious Go project and the second-fastest gateway in every run we have recorded. GoModel is an independent, vendor-neutral gateway whose only job is to be the gateway. Measured numbers are from run 20260829-183422 (29 August 2026) of the reproducible benchmark: every gateway from its public Docker image, one at a time, same in-memory mock backend, same AWS c7i.large. Rerun it yourself with one command.
| Category | GoModel | Bifrost |
|---|---|---|
| Measured on the hot path | ||
| Latency overhead (p50) | 2.35 ms | 3.82 ms |
| Latency tail (p99) | 8.80 ms | 27.80 ms |
| Streaming time to first token (p50) | 5.90 ms | 14.80 ms |
| Sustained throughput | 3,610 req/s | 1,992 req/s |
| Peak RAM under load | 42.7 MB | 275.8 MB |
| Efficiency (req/s per CPU %) | 36.5 | 14.7 |
| Cold start to first request | 0.58 s | 8.67 s |
| Docker image (compressed) | 14.4 MB | 81.6 MB |
| Workloads served | 6/6 workloads | 5/6 (Anthropic streaming failed) |
| Beyond the benchmark | ||
| Runtime | One Go binary | Go binary |
| Provider coverage | 31 providers | 23+ providers |
| OpenAI and Anthropic APIs on one endpoint | Chat, Responses, Messages, streaming | OpenAI-compatible; Anthropic streaming idle-bound |
| Guardrails | Included, MIT | Enterprise license |
| Audit logs | Included, MIT | Enterprise license |
| Role-based access | Scoped workflows + virtual keys, MIT | Enterprise license |
| SSO | OIDC in GoModel Pro | SAML / OIDC, enterprise license |
| Budgets, rate limits, virtual keys | Included | Included |
| Caching | Exact + semantic | Exact + semantic |
| MCP gateway | Included | Included (federated auth is enterprise) |
| Multi-node deployment | Replicas on shared Postgres or MongoDB, MIT | Cluster mode, enterprise license |
| Prompt playground | Not a goal | Included |
| Vendor | enterpilot, Inc. - GoModel is the product | Maxim AI - gateway feeds the Maxim eval platform |
| License | MIT | Apache 2.0 core + enterprise license |
Benchmark: 20,000 requests per workload at concurrency 10, five randomized trials on an AWS c7i.large (2 vCPU, 4 GiB). Retries off on both, GoModel's circuit breaker off, per-request logging off everywhere. Bifrost 2.0.0 served the Anthropic Messages workload non-streaming but not streaming, and its Responses streaming trial completed only a quarter of the requests; both count against its workload score. On p50 for plain chat completions the two are close (2.35 vs 3.82 ms) - the gap opens at the tail, in streaming, and in memory.
Both are good choices. The honest split, based on what each project ships under its open-source license today.
Benchmarks are an argument; your traffic is the proof. GoModel speaks the OpenAI and Anthropic APIs natively, so pointing an existing app at it is a base-URL change.
docker run --rm -p 8080:8080 \
-e LOG_FORMAT=text \
-e OPENAI_API_KEY="your-openai-key" \
enterpilot/gomodelfrom openai import OpenAI
client = OpenAI(
base_url="http://localhost:8080/v1",
api_key="your-gomodel-key",
)Full setup, providers, and configuration live in the documentation. Questions? Ask on Discord or book a 30-minute call.