text model comparison
DeepSeek-V4.1-Flash vs Hy4
DeepSeek-V4.1-Flash and Hy4 are both current text models, from DeepSeek and Tencent. DeepSeek-V4.1-Flash is 64% cheaper per 1M input tokens than Hy4, $0.30 vs $0.834. In Tencent's Hy4 launch table, DeepSeek-V4.1-Flash scores 73.8% on DeepSWE v1.1 and Hy4 74.9%.
- Lower price per 1M input tokens
- DeepSeek-V4.1-Flash$0.30 against $0.834
- Newer release
- Hy4Nov 2026 against Sep 2026
Data verified November 5, 2026 · Dataset 2026-11-05
Side by side
DeepSeek-V4.1-Flash and Hy4, line by line
Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.
| Fact | DeepSeek-V4.1-Flash | Hy4 |
|---|---|---|
| Price | ||
| Price per 1M input tokens | $0.30 (better) | $0.834 |
| Price per 1M output tokens | $1.20 (better) | $2.501 |
| Independent benchmarks | ||
| Arena Text | 1476 Elo (#22 of 52) | Not measured |
| Arena WebDev | 1665 Elo (#13 of 46) | Not measured |
| GPQA Diamond | 93.2% (#16 of 41) | Not measured |
| FrontierMath Tiers 1-3 (v2) | 71.2% (#23 of 41) | Not measured |
| SimpleQA Verified | 42.5% (#27 of 38) | Not measured |
| Specs | ||
| Provider | DeepSeek | Tencent |
| Release date | September 10, 2026 | November 4, 2026 |
| Access | API and open weights | API only |
| Context window | 1,000,000 tokens | Not reported |
| Max output | 384,000 tokens | Not reported |
| Input | text, image | text, image |
| Output | text | text |
No independent benchmark has scored both models yet. Each rank counts the current models scored on that benchmark.
Provider results
What the labs report
Results tables a lab published with one of its models, where it lists both DeepSeek-V4.1-Flash and Hy4. These are the lab's own figures, not independent measurements, and each table is read on its own: labs run benchmarks with different harnesses and budgets.
Tencent, Hy4 launch table, November 4, 2026Tencent · 2026-11-05
| Benchmark | DeepSeek-V4.1-Flash | Hy4 |
|---|---|---|
| DeepSWE v1.1 | 73.8% | 74.9% (better) |
| SWE-Marathon v1.1 | 46.3% (better) | 43.8% |
| ProgramBenchalmost solved | 29.0% | 30.0% (better) |
| Terminal-Bench 4.0 | 40.0% | 44.4% (better) |
| FrontierCode 2.0 | 28.5% | 31.0% (better) |
| APEX-Agents v1.1pass@1 | 72.9% | 75.2% (better) |
| Agents' Last Exam v1.1pass rate | 35.3% | 41.0% (better) |
| AutomationBench v1.0.6 | 54.3% | 56.2% (better) |
| HLE-Fullwith tools | 57.1% | 59.1% (better) |
| Terminal-Bench-Science 0.1 | 13.7% | 19.8% (better) |
| PostTrainBench v1.2 | 29.4% | 35.2% (better) |
| OSWorld 2.1full, partial score | 68.4% | 78.9% (better) |
| MMMU-Pro | 76.7% | 78.6% (better) |
| ZeroBench mainwith tools, pass@5 | 51.0% | 55.4% (better) |
Tencent's appendix to the Hy4 announcement, every model at its highest reasoning setting. Where Tencent lists a lab's reported score beside its own run, the score Tencent measured is shown. DeepSeek-V4.1-Flash is the 1017 build. Left out here: Tencent's internal benchmarks, the Hy4 preview column and GLM-5.3 on HLE, which Tencent ran on the text-only subset.
Charts
Against every current text model
Where DeepSeek-V4.1-Flash and Hy4 land among the current models of their task, on every independent benchmark, on price and on context.
Where each stands
Only DeepSeek-V4.1-Flash has a current Arena Text score: #22 of 52. Each bar is the share of current models it beats.
Independent benchmarks
Arena Text
DeepSeek-V4.1-Flash:#22of 52
1,476 Elo · ahead of 57%
Hy4: Not scored
Arena WebDev
DeepSeek-V4.1-Flash:#13of 46
1,665 Elo · ahead of 73%
Hy4: Not scored
GPQA Diamond
DeepSeek-V4.1-Flash:#16of 41
93.2% · ahead of 63%
Hy4: Not scored
FrontierMath Tiers 1-3 (v2)
DeepSeek-V4.1-Flash:#23of 41
71.2% · ahead of 45%
Hy4: Not scored
SimpleQA Verified
DeepSeek-V4.1-Flash:#27of 38
42.5% · ahead of 30%
Hy4: Not scored
Price and context
Price per 1M input tokens
DeepSeek-V4.1-Flash:#11of 55
$0.30 · cheaper than 76%
Hy4:#21of 55
$0.834 · cheaper than 63%
Price per 1M output tokens
DeepSeek-V4.1-Flash:#10of 55
$1.20 · cheaper than 78%
Hy4:#20of 55
$2.501 · cheaper than 65%
Context window
DeepSeek-V4.1-Flash:#26of 64
1M tokens · longer than 22%
Hy4: Not listed
Quality against price
DeepSeek-V4.1-Flash scores 1,476 at $0.525 (blended price per 1M tokens). The line joins the current models no other beats on both price and Arena Text score; hover any point to name it.
Quality against price: the data
| Model | Provider | Blended price per 1M tokens | Arena Text (Elo) |
|---|---|---|---|
| Gemini 4 Carbon | $4 | 1,528 | |
| Gemini 4 Argon | $4 | 1,520 | |
| Claude Opus 5.5 | Anthropic | $8 | 1,509 |
| Muse Wonder | Meta | $8 | 1,507 |
| Claude Fable 5 | Anthropic | $20 | 1,504 |
| Claude Fable 5.1 | Anthropic | $20 | 1,504 |
| Gemini 3.8 Flash | $1.50 | 1,496 | |
| Muse Spark 1.3 | Meta | $2 | 1,495 |
| Claude Opus 5 | Anthropic | $10 | 1,492 |
| Kimi K3 | Moonshot Kimi | $6 | 1,488 |
| GPT-5.6 Sol | OpenAI | $8 | 1,485 |
| Gemini 3.6 Flash | $3 | 1,483 | |
| GPT-5.5 | OpenAI | $11 | 1,482 |
| Claude Opus 4.8 | Anthropic | $10 | 1,482 |
| Qwen3.8-Max | Alibaba Qwen | $3 | 1,482 |
| GPT-6.1 Sol | OpenAI | $4 | 1,481 |
| GLM-5.3 | Z.ai | $2.15 | 1,481 |
| MiMo-V2.6-Pro | Xiaomi MiMo | $0.54 | 1,480 |
| Claude Sonnet 5.5 | Anthropic | $4 | 1,477 |
| GLM-5.3-Flash | Z.ai | $0.24 | 1,477 |
| GPT-6 Astra | OpenAI | $20 | 1,476 |
| DeepSeek-V4.1-Flash | DeepSeek | $0.52 | 1,476 |
| GPT-5.4 | OpenAI | $5.63 | 1,475 |
| Gemini 3 Flash Preview | $1.13 | 1,473 | |
| Grok 4.20 | xAI | $1.56 | 1,472 |
| GPT-5.6 Terra | OpenAI | $4.50 | 1,467 |
| Grok 4.5 | xAI | $3 | 1,465 |
| DeepSeek-V4-Pro | DeepSeek | $1.98 | 1,465 |
| Claude Sonnet 5 | Anthropic | $4 | 1,462 |
| GPT-6 Sol | OpenAI | $4 | 1,458 |
| Gemini 3.5 Flash-Lite | $0.85 | 1,456 | |
| Grok 4.6 | xAI | $3 | 1,455 |
| GPT-5.6 Luna | OpenAI | $0.45 | 1,453 |
| MiMo-V2.6-Flash | Xiaomi MiMo | $0.18 | 1,448 |
| Step 5 Preview | StepFun | $1.43 | 1,448 |
| Grok 4.3 | xAI | $1.56 | 1,442 |
| GPT-6 Luna | OpenAI | $0.20 | 1,441 |
| Grok 4.7 | xAI | $3 | 1,441 |
| Mistral Large 4 | Mistral AI | $1.05 | 1,432 |
| Claude Haiku 5.5 | Anthropic | $0.20 | 1,425 |
| GPT-4.1 | OpenAI | $3.50 | 1,415 |
| Solar Pro 4 | Upstage | $0.52 | 1,388 |
| GPT-4.1 mini | OpenAI | $0.70 | 1,383 |
| GPT-4.1 nano | OpenAI | $0.18 | 1,322 |
Cost
What each costs
Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.
The same work, priced
For 10M input and 2M output tokens, Hy4 costs 2.5 times as much as DeepSeek-V4.1-Flash, at each provider's listed rates.
10M input and 2M output tokens
Hy4 costs 2.5× as much
- DeepSeek-V4.1-Flash
- $5.40
- Hy4
- $13.34
The same, with 9M of the input tokens cached
Hy4 costs 2.3× as much
- DeepSeek-V4.1-Flash
- $2.75
- Hy4
- $6.21
| Workload or rate | DeepSeek-V4.1-Flash | Hy4 |
|---|---|---|
| Example workloads | ||
| 10M input and 2M output tokens | $5.40 (better) | $13.34 |
| The same, with 9M of the input tokens cached | $2.75 (better) | $6.21 |
| Other listed rates | ||
| 1M input tokens, cached | $0.006 (better) | $0.042 |
| 1M input tokens, off peak | $0.15 | Not listed |
| 1M output tokens, off peak | $0.60 | Not listed |
| 1M input tokens, off-peak, cached | $0.003 | Not listed |
Your own bill will differ. These figures use list prices and example workloads. The AI Model Cost Audit reviews your real usage, shortlists models that score as well for each task for less, and estimates the savings.
Launch price $100, regular price $150
Verdict
When to choose each
DeepSeek-V4.1-Flash
Where it leads
- Lower input and output prices, $0.30 and $1.20 vs $0.834 and $2.501 per 1M tokens
- Open weights you can run yourself
- Cheaper cached input, $0.006 vs $0.042 per 1M tokens
Best for
- High-volume agent and multimodal workloads where per-token cost dominates
- Teams that want a frontier-adjacent model they can also self-host under MIT terms
Watch out for
- The recorded API rates are the peak-hour prices; DeepSeek charges half outside 01:00-04:00 and 06:00-10:00 UTC on weekdays
- Running the open weights moves cost to your own infrastructure, which the token rates here do not represent
- Epoch AI and Arena WebDev scored build 1017, which the API serves; Arena Text has rated only the September build so far
Hy4
Where it leads
No measured lead over DeepSeek-V4.1-Flash in this data.
Best for
- Agents that work across terminals, desktop apps and browsers on a tight budget
- Finance and office work: research reports, spreadsheets and slides
Watch out for
- API only for now: Tencent says it will publish the weights and a system card later, and only Hy4 preview (August 2026, Apache 2.0) is open today
- In Tencent's own table it scores 44.4% on Terminal-Bench 4.0 against 66.8% for Kimi K3.1 Pro, and Tencent says a clear gap remains to top proprietary models on research-level math, long-horizon coding and hard visual questions
- Tencent publishes no context window or output limit for Hy4 (the preview card lists 1M tokens), and no independent benchmark score is recorded here yet
From benchmark to production
Building on DeepSeek-V4.1-Flash or Hy4?
Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.
AI Model Cost AuditLaunch price $100, regular price $150What the audit includes
FAQ
DeepSeek-V4.1-Flash vs Hy4 FAQ
Which is cheaper, DeepSeek-V4.1-Flash or Hy4?
DeepSeek-V4.1-Flash is 64% cheaper per 1M input tokens than Hy4, $0.30 vs $0.834. For 10M input and 2M output tokens, DeepSeek-V4.1-Flash costs $5.40 and Hy4 $13.34 at standard rates.
Which is cheaper with prompt caching, DeepSeek-V4.1-Flash or Hy4?
DeepSeek-V4.1-Flash charges $0.006 per 1M cached input tokens, 98% below its standard input rate, and Hy4 $0.042, 95% below. With 9M of 10M input tokens cached and 2M output tokens, DeepSeek-V4.1-Flash costs $2.75 and Hy4 $6.21.
How do DeepSeek-V4.1-Flash and Hy4 compare in Tencent's own results?
In Hy4 launch table (November 4, 2026), Hy4 leads on DeepSWE v1.1, 74.9% to 73.8%; DeepSeek-V4.1-Flash leads on SWE-Marathon v1.1, 46.3% to 43.8%; Hy4 leads on ProgramBench (almost solved), 30.0% to 29.0%. These are Tencent's figures, not independent measurements.
Can I run DeepSeek-V4.1-Flash or Hy4 myself?
DeepSeek-V4.1-Flash is released as open weights you can run yourself; Hy4 is available through its provider's API only.
Further reading
More on DeepSeek-V4.1-Flash and Hy4
Articles on DeepSeek-V4.1-Flash and Hy4
- DeepSeek V4.1 Flash 1017: What Changed and Why Chips FellOctober 19, 2026
Related comparisons
- Claude Haiku 5.5 vs DeepSeek-V4.1-Flash
- Claude Opus 5.5 vs Hy4
- DeepSeek-V4.1-Flash vs GPT-6 Luna
- Gemini 3.8 Flash vs Hy4
- DeepSeek-V4.1-Flash vs GPT-6 Sol
- GLM-5.3-Flash vs Hy4
- Claude Sonnet 5 vs DeepSeek-V4.1-Flash
- GLM-5.3 vs Hy4
- DeepSeek-V4.1-Flash vs DeepSeek-V4-Pro
- GPT-6.1 Sol vs Hy4
- DeepSeek-V4.1-Flash vs Gemini 3.7 Flash
- GPT-6.1 Terra vs Hy4
Production evaluation
Choosing between DeepSeek-V4.1-Flash and Hy4?
Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- A head-to-head evaluation on your real workload
- Routing between models by cost and difficulty