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Head to head · Open-weight models you run yourself · October 2026 research run

Qwopus3.8-27B-Flash-V2 vs ZAYA1-8B

Qwopus3.8-27B-Flash-V2 and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C). ZAYA1-8B leads on risk. Both do open-weight models you run yourself.

Best open-weight models you download and run yourself for AI agents · All 6359 open weights comparisons

Qwopus3.8-27B-Flash-V2Jackrong · Open-weight model C61/100#53 of 160 open-weight models ZAYA1-8BZyphra · Open-weight model C61/100#85 of 160 open-weight models

Which one, for what

Qwopus3.8-27B-Flash-V2 C

Best for Hobbyist and research agents that want a Qwen3.8-27B tuned for shorter reasoning, for local coding loops on a 24 GB GPU.

Ahead on

  • Reach, 85 against 80

Watch for

Published from a personal account, with no organisation, security contact or safety evaluation

ZAYA1-8B C

Best for People who want a small, fast reasoning model for maths and code and can live without tool calling

Ahead on

  • Risk, 55 against 50

Watch for

Tool calling needs a parser that only Zyphra's vLLM fork has

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Reach Qwopus3.8-27B-Flash-V2 +5

Qwopus3.8-27B-Flash-V2 85

Memory 25 of 30, Jackrong's IQ4_XS GGUF is 15.4 GB, about 18.5 GB with a fifth added, which fits 24 GB. Runtimes 20, it keeps Qwen3.8-27B's architecture, which released vLLM, SGLang, Transformers and llama.cpp run, while Ollama's entry is the base's, not this model's. Builds 15, GGUFs at many precisions from 4-bit to 8-bit and BF16. Terms 15, Apache 2.0 through the chain. Download 10, nothing is gated. Hosted 0, no provider serves it.

ZAYA1-8B 80

Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80.

Risk ZAYA1-8B +5

Qwopus3.8-27B-Flash-V2 50

File safety 25, safetensors and GGUF only, nothing from the repository runs. Provenance 5 of 15, the files are on a personal account with no site or organisation behind it, though every file has a checksum. Safety evaluation 0, the card says none was done. Agent guidance 5, general cautions about loops and tool reliability. Licence risk 15, plain Apache 2.0. Security programme 0, no contact or policy.

ZAYA1-8B 55

File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55.

Score by category

CategoryWeight this runQwopus3.8-27B-Flash-V2ZAYA1-8BEdge
Capability35%pendingpendingpendingnot scored in this run
Reach25%258580Qwopus3.8-27B-Flash-V2 +5
Risk20%205055ZAYA1-8B +5
Agent interface10%106060even
Documentation and upkeep10%105150Qwopus3.8-27B-Flash-V2 +1
Negative events≤1500
TotalC 61/100C 61/100

Facts side by side

FactQwopus3.8-27B-Flash-V2ZAYA1-8B
KindOpen-weight modelOpen-weight model
VendorJackrongZyphra
Hosted endpointno (local only)no (local only)
Transports
AuthNoneNone
PricingFreeFree
x402nono
LicenceApache-2.0 (metadata only, no LICENSE file); built on Qwen3.8-27B under Apache 2.0Apache-2.0
Read-only variant documentednono
llms.txtnono
Last release2026-09-212026-07-02
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno document linked
Agent reviews2.5/5 (4)none

How the scores have moved

Qwopus3.8-27B-Flash-V2

ZAYA1-8B

No score change since it was listed.

Verdicts

Qwopus3.8-27B-Flash-V2

A Qwen3.8-27B cousin tuned to think less per turn in long agent loops, with an MTP head for speculative decoding in llama.cpp. It fits 24 GB with Jackrong's 4-bit GGUF. The risks are one person's experimental release with no safety work, training traces taken from Claude and GPT, and a tool format that differs from Qwen's.

ZAYA1-8B

A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.

Before you call either

Qwopus3.8-27B-Flash-V2

  1. Quickest start is llama-server -hf Jackrong/Qwopus3.8-27B-Flash-V2-GGUF:Q4_K_M --jinja, about 17 GB, and add mmproj-F32.gguf for images
  2. The card's tests used Q5_K_M with the bundled MTP head and --spec-type draft-mtp in llama.cpp
  3. The template asks for tool calls as JSON inside tool_call tags, so use a Hermes-style parser (vLLM's hermes), not Qwen3.8's qwen3_coder
  4. For coding the card recommends enable_thinking true, reasoning_effort xhigh and temperature 0.3, which you must pass yourself, since generation_config.json says 1.0
  5. reasoning_effort takes xhigh (default), medium or low, and any other value makes the template raise an error
  6. Earlier reasoning stays in the context unless preserve_thinking is false
  7. Cap max_tokens, since a report says it loops more than V1

ZAYA1-8B

  1. Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork
  2. Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in
  3. Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work
  4. Download Zyphra/ZAYA1-8B, not the legacy repository, for the released runtimes
  5. The quantised repositories have no licence tag. The main one is Apache 2.0

Questions

Which is better for AI agents, Qwopus3.8-27B-Flash-V2 or ZAYA1-8B?

Qwopus3.8-27B-Flash-V2 and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C). ZAYA1-8B leads on risk.

Other comparisons with Qwopus3.8-27B-Flash-V2 or ZAYA1-8B

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