Compare / head-to-head
GPT-6 Astravs
Hunyuan-A13B-Instruct
GPT-6 Astra and Hunyuan-A13B-Instruct do not yet share a public benchmark, so quality cannot be compared apples-to-apples. GPT-6 Astra has the larger context window (1.1M tokens).
Benchmarks from cited public sources; pricing from official pages; status from official provider feeds.
Shared benchmarks
0
no overlap yet
Cheaper per token
—
list price, input + output
Larger context
GPT-6 Astra
1.1M tokens
Providers
2 providers
OpenAI · Tencent Hunyuan
GPT-6 Astra
OpenAI · released 2026-09-03
textvision
Hunyuan-A13B-Instruct
Tencent Hunyuan · released 2025-06-27
text
- Context
- 262K
- Max out
- —
- Input /1M
- —
- Output /1M
- —
- Cached /1M
- —
- Scores
- 15 · 3 core
Quality
Benchmark matrix
0 shared · 33 only GPT-6 Astra · 15 only Hunyuan-A13B-Instruct| Benchmark | GPT-6 Astra | Hunyuan-A13B-Instruct | Δ | Edge |
|---|---|---|---|---|
| Reported by both · 0 | ||||
| No public benchmark is reported for both models yet. | ||||
| Only GPT-6 Astra reports · 33 | ||||
| GPQA Diamond | 96% ↗ | not reported | — | — |
| LMArena Elo | 1477.1 ↗ | not reported | — | — |
| APEX-Agents (Mercor) | 64.7% ↗ | not reported | — | — |
| AutomationBench 1.0.6 | 41.4% ↗ | not reported | — | — |
| BALROG (BALROG) | 68.3% ↗ | not reported | — | — |
| Chess Puzzles (Epoch AI run) | 72% ↗epoch run | not reported | — | — |
| DeepSWE v1.1 (Datacurve) | 74.1% ↗ | not reported | — | — |
| EBR-bench (Epoch AI run) | 76.2% ↗epoch run | not reported | — | — |
| FrontierMath Tier 4 v2 (Epoch AI run) | 97.6% ↗epoch run | not reported | — | — |
| FrontierMath Tiers 1-3 v2 (Epoch AI run) | 93.7% ↗epoch run | not reported | — | — |
| FrontierSWE V2 (Proximal Labs) | 65.5% ↗ | not reported | — | — |
| Furniture Assembly (Epoch AI run) | 80% ↗epoch run | not reported | — | — |
| GSO Opt@1 (GSO) | 77.5% ↗ | not reported | — | — |
| LiveBench Agentic Coding (LiveBench) | 57.3% ↗ | not reported | — | — |
| LiveBench Coding (LiveBench) | 80.4% ↗ | not reported | — | — |
| LiveBench Data Analysis (LiveBench) | 83% ↗ | not reported | — | — |
| LiveBench Instruction Following (LiveBench) | 75.6% ↗ | not reported | — | — |
| LiveBench Language (LiveBench) | 89.4% ↗ | not reported | — | — |
| LiveBench Mathematics (LiveBench) | 96.8% ↗ | not reported | — | — |
| LiveBench Reasoning (LiveBench) | 92.7% ↗ | not reported | — | — |
| LMArena Agent (LMArena) | 0.1227 ↗ | not reported | — | — |
| LMArena Vision (LMArena) | 1284.3 ↗ | not reported | — | — |
| LMArena WebDev (LMArena) | 1787.7 ↗ | not reported | — | — |
| MirrorCode (Epoch AI run) | 46.7% ↗epoch run | not reported | — | — |
| Mystery Game Puzzles (Epoch AI run) | 84% ↗epoch run | not reported | — | — |
| OTIS Mock AIME 2024-2025 (Epoch AI run) | 100% ↗epoch run | not reported | — | — |
| SAGE (Vals AI) | 46.4% ↗ | not reported | — | — |
| SimpleBench (SimpleBench) | 86.5% ↗ | not reported | — | — |
| SimpleQA Verified | 75.6% ↗epoch run | not reported | — | — |
| Terminal-Bench 4.0 (Vals AI) | 59.6% ↗ | not reported | — | — |
| Terminal-Bench Science 0.1 | 64.6% ↗ | not reported | — | — |
| Vending-Bench 2 (Andon Labs) | 15514.7 ↗ | not reported | — | — |
| WeirdML (Håvard Tveit Ihle) | 93.6% ↗ | not reported | — | — |
| Only Hunyuan-A13B-Instruct reports · 15 | ||||
| AIME 2025 | not reported | 76.8% ↗ | — | — |
| AIME 2024 | not reported | 87.3% ↗ | — | — |
| ArtifactsBench | not reported | 43% ↗ | — | — |
| BBH | not reported | 89.1% ↗ | — | — |
| BFCL v3 | not reported | 78.3% ↗ | — | — |
| C3-Bench | not reported | 63.5% ↗ | — | — |
| ComplexFuncBench | not reported | 61.2% ↗ | — | — |
| Fullstackbench | not reported | 67.8% ↗ | — | — |
| GPQA-Diamond | not reported | 71.2% ↗ | — | — |
| IF-Eval | not reported | 84.7% ↗ | — | — |
| Livecodebench | not reported | 63.9% ↗ | — | — |
| MATH | not reported | 94.3% ↗ | — | — |
| OlympiadBench | not reported | 82.7% ↗ | — | — |
| ZebraLogic | not reported | 84.7% ↗ | — | — |
| τ-Bench | not reported | 54.7% ↗ | — | — |
Scores tagged "epoch" or "matharena" are independent runs, used only where the lab has not published its own; ⚠ marks rows MathArena flags as released after the competition. Higher is better on every row. Δ is GPT-6 Astra minus Hunyuan-A13B-Instruct in the benchmark's own unit. "Not reported" means the lab has not published that figure; it is not a zero. ↗ opens the source.
Specs & pricing
Side by side
Official pricing pages and model cards| Spec | GPT-6 Astra | Hunyuan-A13B-Instruct | Edge |
|---|---|---|---|
| Context window | 1.1M tokens | 262K tokens | GPT-6 Astra |
| Max output | 128K tokens | — | — |
| Input price / 1M | $10 ↗ | — | — |
| Output price / 1M | $50 ↗ | — | — |
| Cached input / 1M | $1 ↗ | — | — |
| Input + output / 1M Lower is cheaper. List prices; batch, tool and regional fees excluded. | $60 | — | — |
| Modalities | text · vision | text | GPT-6 Astra |
| Released | 2026-09-03 | 2025-06-27 | — |
| Cited benchmark scores | 39 | 15 | — |
Reliability
Provider status
Live from /statusMore matchups
GPT-6 Astra vs …
Models sharing the most benchmarksMore matchups
Hunyuan-A13B-Instruct vs …
Models sharing the most benchmarksBuilt by Respan
Which one wins on your data?
Public benchmarks are a starting point. Run GPT-6 Astra and Hunyuan-A13B-Instruct on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.