vs
4:0
overall capability wins (0 ties across 4 scored). Hy4 Preview leads overall.
- Reasoning1:0
- Coding1:0
- Specs2:0
Verdict
Hy4 Preview leads coding (widest gap: +57.7 on TermBench); Hy4 Preview offers ~3.8x larger context (1M vs 262K).
- Hy4 Preview leads coding (widest gap: +57.7 on TermBench)
- Hy4 Preview offers ~3.8x larger context (1M vs 262K)
Cost for 1M in + 250K out
Illustrative chat workload at primary-provider list prices.
- Hy4 Preview
- $1.46
- Ling-3.0 Tiny
- -
Price per 1M tokens
Full comparison
Organization
Tencent
InclusionAI
Family
Other
Other
License
Apache 2.0
MIT
Open weights
Yes
Yes
Release
Aug 28, 2026
Aug 17, 2026
Knowledge cutoff
-
-
API / provider
Tencent Cloud TokenHub
No primary API price listed
Modalities
text → text
text → text
Specs
Context window
1M
262K
Max output
-
33K
Parameters
770B (49B act.)
7.9B (1.3B act.)
Pricing
Input $/1M
$0.83
—
Output $/1M
$2.50
—
Blended $/1M (3∶1)
$1.25
-
Speed
tok/s
-
-
TTFT (s)
-
-
Reasoning
MMLU-Pro
—
—
GPQA Diamond
92.3
73.4
Humanity's Last Exam
—
9.3
AIME 2025
—
—
MATH-500
—
—
Humanity's Last Exam (with tools)
—
—
AA-Omniscience Accuracy
—
8.5
AA-LCR v1.1
—
60.3
CritPt
—
—
MMMU-Pro
—
—
IFBench
—
—
Chartography
—
—
Chartography (With Tools)
—
—
Coding
SWE-bench Verified
—
—
SWE-bench Pro
65.7
—
SWE-bench Multilingual
82.9
—
LiveCodeBench
—
—
Terminal-Bench 2.1
85.4
27.7
Aider Polyglot
—
—
Terminal-Bench 3
—
—
BigCodeBench
—
—
SciCode
—
24.2
CursorBench
—
—
SWE-Rebench
—
—
NL2Repo-Bench
—
—
DeepSWE
64.3
—
WebDev Arena
1,624
—
Terminal-Bench 4.0
—
—
CursorBench 4.0
—
—
FrontierCode v1.1 (Main)
—
—
Arena
LMArena Elo
—
—
| Metric | Hy4 Preview | Ling-3.0 Tiny | Delta |
|---|---|---|---|
| Identity | |||
| Organization | Tencent | InclusionAI | — |
| Family | Other | Other | — |
| License | Apache 2.0 | MIT | — |
| Open weights | Yes | Yes | — |
| Release | Aug 28, 2026 | Aug 17, 2026 | — |
| Knowledge cutoff | - | - | — |
| API / provider | Tencent Cloud TokenHub | No primary API price listed | — |
| Modalities | text → text | text → text | — |
| Specs | |||
| Context window | 1M | 262K | A +738K |
| Max output | - | 33K | — |
| Parameters | 770B (49B act.) | 7.9B (1.3B act.) | A +762 |
| Pricing | |||
| Input $/1M | $0.83 | — | — |
| Output $/1M | $2.50 | — | — |
| Blended $/1M (3∶1) | $1.25 | - | — |
| Speed | |||
| tok/s | - | - | — |
| TTFT (s) | - | - | — |
| Reasoning | |||
| MMLU-Pro | — | — | — |
| GPQA Diamond | 92.3 | 73.4 | A +18.9 pts |
| Humanity's Last Exam | — | 9.3 | — |
| AIME 2025 | — | — | — |
| MATH-500 | — | — | — |
| Humanity's Last Exam (with tools) | — | — | — |
| AA-Omniscience Accuracy | — | 8.5 | — |
| AA-LCR v1.1 | — | 60.3 | — |
| CritPt | — | — | — |
| MMMU-Pro | — | — | — |
| IFBench | — | — | — |
| Chartography | — | — | — |
| Chartography (With Tools) | — | — | — |
| Coding | |||
| SWE-bench Verified | — | — | — |
| SWE-bench Pro | 65.7 | — | — |
| SWE-bench Multilingual | 82.9 | — | — |
| LiveCodeBench | — | — | — |
| Terminal-Bench 2.1 | 85.4 | 27.7 | A +57.7 pts |
| Aider Polyglot | — | — | — |
| Terminal-Bench 3 | — | — | — |
| BigCodeBench | — | — | — |
| SciCode | — | 24.2 | — |
| CursorBench | — | — | — |
| SWE-Rebench | — | — | — |
| NL2Repo-Bench | — | — | — |
| DeepSWE | 64.3 | — | — |
| WebDev Arena | 1,624 | — | — |
| Terminal-Bench 4.0 | — | — | — |
| CursorBench 4.0 | — | — | — |
| FrontierCode v1.1 (Main) | — | — | — |
| Arena | |||
| LMArena Elo | — | — | — |
Hy4 Preview
- Context
- 1M
- Parameters
- 770B (49B act.)
- Price
- $0.83 / $2.50
- Speed
- —
- Modalities
- text → text
- License
- Apache 2.0
Tencent Hy Team's Aug 28, 2026 open-weight flagship (770B MoE / 49B active, Apache 2.0) with a 1M context window and default high reasoning effort. Text-only instruct weights on Hugging Face; hosted API at $0.834/$2.501 per 1M tokens via TokenHub and OpenRouter.
Ling-3.0 Tiny
- Context
- 262K / 33K out
- Parameters
- 7.9B (1.3B act.)
- Price
- —
- Speed
- —
- Modalities
- text → text
- License
- MIT
Compact on-device member of InclusionAI's Ling 3.0 family (7.9B total / 1.3B active MoE, MIT) with a hybrid KDA/MLA attention stack, native 256K context, and switchable thinking / instant modes.
Benchmark charts
Winner bars are emphasized. Per-benchmark deltas sit above each chart.