glm-4p7: benchmark scores, price and ranking

glm-4p7 from Z.ai ranks #399 of 743 LLMs on the LLMs Tiger aggregate benchmark score (47.9), based on 1 benchmark results captured up to 2026-10-13.

Organisation: Z.ai
Type: Open-weight / local model
Open weights: Yes
Cheapest API price: $0.600 in / $2.20 out per million tokens (via fireworks_ai, observed 2026-10-13T20:47Z)
Aggregate rank: #399 of 743 (score 47.9)

Across the 1 benchmark where at least ten models are scored, glm-4p7 is in the top 10% on 0 and in the top half on 0.

Its cheapest listed input price, $0.600 per million tokens, is lower than that of 45% of the 427 models with a listed price.

glm-4p7 benchmark results

glm-4p7 benchmark scores, ranked against all models measured on each benchmark
Benchmark	Score	Rank	Source	Captured
MCP Atlas	58.1%	#11 of 14	Scale Labs MCP Atlas leaderboard	2026-10-13

About glm-4p7

glm-4p7 is an open-weight model that can run on your own hardware from Z.ai. The cheapest API listing we track charges $0.600 per million input tokens and $2.20 per million output tokens, through fireworks_ai. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.

Where glm-4p7 stands

On our aggregate score, glm-4p7 is #399 of 743 ranked models, around the middle of the table. Its score is 47.9; the scale is centred on 50, so it sits 2.1 points below the typical model. That beats 46% of the ranked field. Among the 5 ranked Z.ai models it is #5. The next one up is glm-5.2-max at 48.8.

glm-4p7, benchmark by benchmark

glm-4p7 lands below the middle on MCP Atlas: 58.1%, #11 of 14, with 71% of the field scoring higher. Muse Spark leads at 82.2%; the closest result above is kimi-k2p5 at 64.4%. It covers tool use across 1,000 MCP tasks. The board median is 70.4%, so glm-4p7 is 12.3 points below it. Source: Scale Labs MCP Atlas leaderboard, captured 2026-10-13.

Price and value

The median input price across the 427 priced models is $0.500 per million tokens, so glm-4p7 costs more than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on Llama-4-Maverick-17B-128E-Instruct ($0.630) and Kimi K2.6 ($0.650).

Reading these numbers

The 1 score on this page comes from 1 source: Scale Labs MCP Atlas leaderboard (1). 1 of them come from an official leaderboard and 0 from datasets or third-party runs. With 1 results the aggregate rank can move a lot when one new score arrives.

Models ranked nearby

#396 DeepSeek-V3.2 (Thinking; Fireworks) (47.9)
#397 qwen3-235b-a22b (47.9)
#398 Opus 4.5 (Thinking, None) (47.9)
#400 gemini-2.0-flash-thinking-exp-01-21 (47.9)
#401 Kimi K2 Thinking (47.8)
#402 GPT-5.1 (Thinking, Medium) (47.8)