Model comparison
Qwen3.8 27B vs Yi-34B
Qwen3.8 27B is the stronger model overall, scoring 46.0 to 27.8 on the Noometry Index.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. Qwen3.8 27B scores higher in 8 categories and Yi-34B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.8 27B leads 41.6 to 7.5.
Side by side
| Qwen3.8 27B | Yi-34B | |
|---|---|---|
| Provider | Alibaba (Qwen) | 01.AI |
| Noometry Index | 46.0 | 27.8 |
| Released | 2026-08-14 | 2023-11-02 |
| Weights | Open | Open |
| Context window | 262K | — |
| Max output | 33K | — |
| Input $ / M tokens | $0.04 | — |
| Output $ / M tokens | $2.30 | — |
| Results tracked | 31 | 23 |
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Category by category
Coding Qwen3.8 27B leads
Qwen3.8 27B: 50.5 (#44), Yi-34B: 32.3 (#274)
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Coding | 1482 | 1112 |
| LMArena WebDev | 1593 | — |
| SciCode | 46.6% | — |
Agentic & Tool Use Not comparable
Qwen3.8 27B: 32.9 (#57), Yi-34B: —
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| APEX-Agents | 47.5% | — |
Reasoning Qwen3.8 27B leads
Qwen3.8 27B: 41.0 (#54), Yi-34B: 21.2 (#226)
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Hard Prompts | 1460 | 1104 |
| Epoch Capabilities Index | 149.38 | 117.39 |
| ARC-AGI-2 | 42.4% | — |
| NYT Connections (extended) | 54.5% | — |
| ARC-AGI-1 | 87.5% | — |
| CritPt | 5.4% | — |
| DTBench | 88% | — |
| LMCA | 41.4% | — |
| Surface Evolver Bench | 45% | — |
| BIG-Bench Hard | — | 71.7% |
Math Qwen3.8 27B leads
Qwen3.8 27B: 37.1 (#161), Yi-34B: 21.6 (#282)
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Math | 1456 | 1114 |
| ProofBench | 16% | — |
| MATH Level 5 | — | 5.1% |
| GSM8K | — | 76% |
Knowledge Qwen3.8 27B leads
Qwen3.8 27B: 41.6 (#109), Yi-34B: 7.5 (#309)
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Expert | 1482 | 1061 |
| GPQA Diamond | — | 14.7% |
| MMLU | — | 76.3% |
Multimodal Not comparable
Qwen3.8 27B: 41.3 (#37), Yi-34B: —
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Vision | 1271 | — |
Multilingual Qwen3.8 27B leads
Qwen3.8 27B: 53.7 (#60), Yi-34B: 29.7 (#264)
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Non-English | 1430 | 1079 |
| LMArena Chinese | 1504 | 1176 |
| LMArena French | 1465 | 1081 |
| LMArena German | 1438 | 1042 |
| LMArena Japanese | 1384 | 993 |
| LMArena Korean | 1393 | 959 |
| LMArena Russian | 1415 | 1050 |
| LMArena Spanish | 1448 | 1070 |
Instruction Following Qwen3.8 27B leads
Qwen3.8 27B: 75.8 (#53), Yi-34B: 56.2 (#274)
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Instruction Following | 1439 | 1091 |
Long Context Qwen3.8 27B leads
Qwen3.8 27B: 44.3 (#70), Yi-34B: 33.2 (#264)
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Longer Query | 1450 | 1094 |
Writing & Preference Qwen3.8 27B leads
Qwen3.8 27B: 65.8 (#43), Yi-34B: 34.1 (#273)
| Benchmark | Qwen3.8 27B | Yi-34B |
|---|---|---|
| LMArena Text | 1441 | 1129 |
| LMArena Creative Writing | 1384 | 1108 |
| LMArena Multi-Turn | 1441 | 1113 |
| EQ-Bench Creative Writing | 1671 | — |
Frequently asked questions
Is Qwen3.8 27B better than Yi-34B?
Qwen3.8 27B is the stronger model overall, scoring 46.0 to 27.8 on the Noometry Index.
Is Qwen3.8 27B or Yi-34B better for coding?
Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 32.3 in the Noometry coding category.
How many benchmarks do Qwen3.8 27B and Yi-34B share?
18 benchmarks have published results for both models. Qwen3.8 27B has 31 scored results on Noometry and Yi-34B has 23.