ZAYA1-8B
BenchLM is tracking ZAYA1-8B, but this profile is currently excluded from the public leaderboard because it still lacks enough non-generated benchmark coverage to rank safely. Only non-generated public benchmark rows appear below.
ZAYA1-8B is a open weight model with a 131K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.
This profile currently has 12 of 186 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Instruction Following (#83). This performance profile makes it a well-rounded choice across a range of tasks.
Ranking Distribution
Category rank across 2 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
Coding
Reasoning
Knowledge
Math
Multilingual
Multimodal
Inst. Following
#83Benchmark Details
Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.
Compare This Model
See how ZAYA1-8B stacks up against similar models
Frequently Asked Questions
How does ZAYA1-8B perform overall in AI benchmarks?
ZAYA1-8B has 12 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is ZAYA1-8B good for knowledge and understanding?
ZAYA1-8B has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is ZAYA1-8B good for coding and programming?
ZAYA1-8B has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.
Is ZAYA1-8B good for mathematics?
ZAYA1-8B has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is ZAYA1-8B good for agentic tool use and computer tasks?
ZAYA1-8B has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is ZAYA1-8B good for instruction following?
ZAYA1-8B ranks #83 out of 115 models in instruction following benchmarks with an average score of 44.7. There are stronger options in this category.
Is ZAYA1-8B open source?
Yes, ZAYA1-8B is an open weight model created by Zyphra, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does ZAYA1-8B have full benchmark coverage on BenchLM?
Not yet. ZAYA1-8B currently has 12 published benchmark scores out of the 186 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of ZAYA1-8B?
ZAYA1-8B has a context window of 131K, which determines how much text it can process in a single interaction.
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