the models · 65

Every model, one room.

The union of the wire catalog: each model names the providers that serve it, the window it reads, the exact-match price rows and the measured energy rows. What the catalog does not carry, the room says plainly · a missing number is a fact, never a zero.

Vendored from the released binary · supernovae-st/nika@f3a31a6ee007 (v0.118.7) · digest-verified, re-derived at build, gated in CI

The bench

1 published receipt: a room shows a measured answer only when a receipt names its model, with the evidence pack served beside it. Every other seat: run it yourself · the model-bench workflow in the public registry measures YOUR machine, and the first receipt shows what an honest one looks like.

The context axis

The axis draws the canonical catalog · the spec-named seats whose models declare a window. The register below is the wider wire union; each count names its facet.

Loading the context axis…

The price axis

Every priced model, seated at its cheapest recorded output seat. The taller accent ticks are open weights: the seats you could also host yourself.

13 priced · $0.08 → $15 out/Mtok · log scale · 6 open weights

The register

@cf/meta/llama-3.1-8b-instruct128k
cloudflare
@cf/meta/llama-3.3-70b-instruct-fp8-fast128k
cloudflare
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sambanova
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sambanova
MiniMax-M2245k
minimax
MiniMax-VL-01100k
minimax
Qwen/Qwen3-8B128k
native · vllm
Qwen/Qwen3.5-397B-A17B:fastest262k
huggingface
Qwen/Qwen3.5-9B:cheapest262k
huggingface
accounts/fireworks/models/llama-v3p1-8b-instruct128k
fireworks
accounts/fireworks/models/llama-v3p3-70b-instruct128k
fireworks
anthropic.claude-haiku-4-5-20251001-v1:0128k
bedrock
anthropic.claude-sonnet-4-6-v1:0128k
bedrock
anthropic/claude-haiku-4-5-20251001128k
openrouter
anthropic/claude-sonnet-4-6128k
openrouter
claude-haiku-4-5-20251001200k$5
anthropic
claude-sonnet-4-6200k$15
anthropic
command-r128k
cohere
command-r-plus128k
cohere
databricks-meta-llama-3-1-70b-instruct128k
databricks
deepseek-chat64k$0.28open weights
deepseek
default128k
llamacpp · localai
echo1m
mock
gemini-2.0-flash1.0m
gemini · vertex
gemini-2.5-flash1.0m
gemini · vertex
glm-4-flash128k
zhipu
glm-4.5128k
zhipu
gpt-4o128k
azure
gpt-4o-mini128k$0.6
azure · openai
gpt-5-mini272k$2
openai
gpt-5.2272k$14
openai
grok-3131k$15
xai
grok-3-mini-fast131k$4
xai
jamba-1.5-large256k
ai21
jamba-1.5-mini256k
ai21
kimi-k2128k
moonshot
kimi-k2.5256k
moonshot
llama-3.1-8b128k
cerebras
llama-3.1-8b-instant128k$0.08open weights
groq
llama-3.3-70b128k
cerebras
llama-3.3-70b-versatile128k$0.79open weights
groq
llama3.2:3b128k
ollama
meta-llama/Llama-3.1-8B-Instruct-Turbo128k
together
meta-llama/Llama-3.3-70B-Instruct128k
hyperbolic
meta-llama/Llama-3.3-70B-Instruct-Turbo128k
together
meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP81.0m
deepinfra
meta-llama/Meta-Llama-3.1-8B-Instruct128k
deepinfra
meta/llama-3.1-70b-instruct128kopen weights
nvidia
meta/meta-llama-3-70b-instruct8k
replicate
meta/meta-llama-3-8b-instruct8k
replicate
mistral-large-latest128k$1.5open weights
mistral
mistral-small-latest32k$0.6open weights
mistral
mock-default1m
mock
nvidia/nemotron-3-nano-30b-a3b262kopen weights
nvidia
nvidia/nemotron-3-super-120b-a12b262k$0.8open weights
nvidia
palmyra-x-004128k
writer
qwen-max32k
qwen
qwen-turbo1m
qwen
qwen-vl-plus32k
qwen
qwen3.5-4b128k
lmstudio
qwen3.5:4b128k
ollama
sonar128k
perplexity
sonar-pro200k
perplexity
voyage-3-large32k
voyage
voyage-3-lite32k
voyage

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