Head to head
Qwen3.8-27B vs Gemma 3 27B
Qwen3.8-27B from Alibaba Qwen against Gemma 3 27B from Google DeepMind — specification, price and every benchmark both makers have published, in one table.
At a glance
Benchmarks
Qwen3.8-27B leads
Qwen3.8-27B wins 1 of the 1 benchmarks both models report, Gemma 3 27B wins 0, by a wide margin. The average gap across shared tests is 46.8 points.
Price
Not directly comparable
At least one of these does not have a published per-token price, so cost cannot be compared like for like. The open-weight model can be run on your own hardware instead.
What actually differs
- These two are closely matched on the specification side — same broad capabilities, same licensing posture. The decision comes down to the benchmark rows and the price.
Scorecard
Which is better at what
Maths, coding, reasoning and the rest — one line each, averaged over the benchmarks both models actually report.
| Category | Qwen3.8-27B | Gemma 3 27B | Better at this |
|---|---|---|---|
| ReasoningGPQA Diamond | 89.2% | 42.4% | Qwen3.8-27B+46.8 |
| MathsNeither model reports this | — | — | Not comparable |
| CodingOnly one model reports this | — | — | Not comparable |
| KnowledgeOnly one model reports this | — | — | Not comparable |
| MultimodalOnly one model reports this | — | — | Not comparable |
| Instruction followingNeither model reports this | — | — | Not comparable |
| Human preferenceOnly one model reports this | — | — | Not comparable |
| Categories wonOut of 1 comparable | 1 | 0 | Qwen3.8-27B |
Each category averages only the benchmarks every model here reports, so no one is credited for a test the other did not run. A category with no shared test is marked Not comparable rather than guessed at.
Side by side
Qwen3.8-27B and Gemma 3 27B, row by row
| Attribute | Qwen3.8-27BAlibaba Qwen | Gemma 3 27BGoogle DeepMind |
|---|---|---|
| Specification | ||
| MakerWho built it | Alibaba Qwen | Google DeepMind |
| Released | 2026-08 | 2025-03 |
| ParametersTotal, and active per token for a mixture of experts | 27B | 27B |
| Architecture | Dense transformer | Dense transformer |
| Context windowHow much can go in at once | Not reported | 131,072 tokens |
| Max output | Not reported | 8,192 tokens |
| Input | Not reported | Text, Image |
| ReasoningSpends extra tokens thinking before it answers | Not reported | No |
| Tool calling | Yes | Yes |
| Licence | Apache 2.0 | Gemma Terms of Use |
| Open weightsCan you download and run it yourself | Yes | Yes |
| Price | ||
| Input priceUSD per million tokens in | Not reported | $0.10 |
| Output priceUSD per million tokens out | Not reported | $0.20 |
| Blended 3:1A 3-in-to-1-out million-token mix — a fairer single number than input price alone | Not reported | $0.125 |
| Price note | First-party API rate. | Open weights — this is a representative hosting rate, not a first-party price. Running it yourself costs only hardware. |
| Published benchmarks | ||
| MMLU-Pro12,000 reasoning-heavy multiple-choice questions across 14 academic subjects, with ten options instead of four. The harder successor to MMLU. | Not reported | |
| GPQA Diamond198 graduate-level physics, chemistry and biology questions written to be Google-proof. PhD holders in the matching field score about 65%. | ||
| SWE-bench ProA harder, contamination-resistant successor to SWE-bench Verified, drawn from commercial and copyleft repositories that were never public training data. | Not reported | |
| HumanEval164 short Python functions written from a docstring. Saturated at the frontier — kept here for continuity with older models. | Not reported | |
| MMMUCollege-level questions that require reading charts, diagrams, tables and photographs alongside the text. | Not reported | |
| LMArena EloElo rating from blind pairwise votes by the public on LMArena. Measures what people prefer, not what is correct. | Not reported | |
| Links | Full page | Hugging Face · Full page |
| Row verified | 2026-10 | 2026-08 |
Where these numbers come from
Every score on this page is a published figure, taken from the model's own card, system card, technical report or release post, or from a public leaderboard. CorX Labs did not run these evaluations. Most are self-reported by the lab that built the model, which means they were produced under that lab's own choice of prompt, scaffold and number of attempts — so treat them as a starting point for a shortlist, not as a settled ranking.
A score someone other than the model's maker measured is marked Independent and names its measurer. Those are the stronger numbers on this page — an outside harness has no reason to flatter anyone — and there are not many of them.
Where a figure has not been published, the cell reads Not reported rather than an estimate. Nothing here is inferred, interpolated or guessed. Each model records the month its row was last checked. Full method and caveats.
Questions
Qwen3.8-27B or Gemma 3 27B?
Is Qwen3.8-27B better than Gemma 3 27B?
Qwen3.8-27B wins 1 of the 1 benchmarks both models report, Gemma 3 27B wins 0, by a wide margin. The average gap across shared tests is 46.8 points.
Which is cheaper, Qwen3.8-27B or Gemma 3 27B?
At least one of these does not have a published per-token price, so cost cannot be compared like for like. The open-weight model can be run on your own hardware instead.
What is the difference between Qwen3.8-27B and Gemma 3 27B?
These two are closely matched on the specification side — same broad capabilities, same licensing posture. The decision comes down to the benchmark rows and the price.
