DeepSeek V4 Flash vs DeepSeek V4 Flash 0731 vs Qwen3.5 Flash
Too close to call on our weighted score (DeepSeek V4 Flash 0731 76, Qwen3.5 Flash 75, DeepSeek V4 Flash 71). The right pick depends on what you value most.
DeepSeekDeepSeek V4 Flash
71/100- ECI146.1
- Price$0.14 / $0.28
- Context1M
- DeepSeek
DeepSeek V4 Flash 0731
76/100- ECI154.5
- Price$0.14 / $0.28
- Context1M
Alibaba (Qwen)Qwen3.5 Flash
75/100- ECI144.0
- Price$0.10 / $0.40
- Context1M
Too close to call
It is close. Our weighted score puts them within 1 points (DeepSeek V4 Flash 0731 76/100, Qwen3.5 Flash 75/100, DeepSeek V4 Flash 71/100), so choose by what matters most for your work: DeepSeek V4 Flash 0731 for raw capability and DeepSeek V4 Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek V4 Flash 0731Capabilities Index (ECI): DeepSeek V4 Flash 0731 154.5 · DeepSeek V4 Flash 146.1 · Qwen3.5 Flash 144.0
- Lowest priceSame priceDeepSeek V4 Flash $0.175 · DeepSeek V4 Flash 0731 $0.175 · Qwen3.5 Flash $0.175 per 1M tokens (3:1 blend)
- Longest contextAbout the sameDeepSeek V4 Flash 1,000,000 · DeepSeek V4 Flash 0731 1,000,000 · Qwen3.5 Flash 1,000,000 tokens
- Widest inputsQwen3.5 FlashDeepSeek V4 Flash: Text · DeepSeek V4 Flash 0731: Text · Qwen3.5 Flash: Text, Images, Video
- Self-hostingDeepSeek V4 Flash and DeepSeek V4 Flash 0731Publishes downloadable weights (MIT)
| Measure | Weight | DeepSeek V4 Flash | DeepSeek V4 Flash 0731 | Qwen3.5 Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 73 | 84 | 71 |
| Price | 25% | 86 | 86 | 86 |
| Inputs & features | 15% | 45 | 45 | 80 |
| Context window | 10% | 60 | 60 | 60 |
| Overall | 100% | 71/100 | 76/100 | 75/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek V4 FlashDeepSeek | DeepSeek V4 Flash 0731DeepSeek | Qwen3.5 FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 146.1 | 154.5 (best) | 144.0 |
| ECI rank | #71 of 148 | #32 of 148 (best) | #82 of 148 |
| GPQA DiamondGraduate-level science questions | — | 91.0% (best) | 82.3% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 57.5% (best) | 18.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 94.4% (best) | 84.4% |
| SimpleQA VerifiedShort factual questions | — | 33.6% (best) | 20.3% |
| Price per million tokens | |||
| Input | $0.14 | $0.14 | $0.10 (best) |
| Output | $0.28 (best) | $0.28 (best) | $0.40 |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.175 | $0.175 | $0.175 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 42 providers | Median of 48 providers | Official Alibaba API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 384,000 tokens (best) | 384,000 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | OpenMIT | Proprietary |
| API model ID | — | — | qwen3.5-flash |
| API providers | 48 | 49 (best) | 8 |
| Released | Apr 24, 2026 | Jul 31, 2026 | Feb 23, 2026 |
| Knowledge cutoff | May 2025 | May 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek V4 Flash$1.96
- DeepSeek V4 Flash 0731$1.96
- Qwen3.5 Flash$1.80
Which should you choose?
Which is better: DeepSeek V4 Flash, DeepSeek V4 Flash 0731 or Qwen3.5 Flash?
It is close. Our weighted score puts them within 1 points (DeepSeek V4 Flash 0731 76/100, Qwen3.5 Flash 75/100, DeepSeek V4 Flash 71/100), so choose by what matters most for your work: DeepSeek V4 Flash 0731 for raw capability and DeepSeek V4 Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek V4 Flash, DeepSeek V4 Flash 0731 or Qwen3.5 Flash?
DeepSeek V4 Flash, DeepSeek V4 Flash 0731 and Qwen3.5 Flash cost the same: $0.14 input / $0.28 output per million tokens.
Which scores higher on benchmarks?
DeepSeek V4 Flash 0731 scores higher on the Capabilities Index (ECI): DeepSeek V4 Flash 0731 154.5 (#32 of 148), DeepSeek V4 Flash 146.1 (#71 of 148) and Qwen3.5 Flash 144.0 (#82 of 148). Their confidence ranges do not overlap (152.0–156.6 vs 143.6–147.9), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4 Flash, DeepSeek V4 Flash 0731 and Qwen3.5 Flash yet, so there is no like-for-like coding score. On overall capability, DeepSeek V4 Flash 0731 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
DeepSeek V4 Flash, DeepSeek V4 Flash 0731 and Qwen3.5 Flash share the same 1,000,000-token context window. Maximum output per response: DeepSeek V4 Flash up to 384,000, DeepSeek V4 Flash 0731 up to 384,000, Qwen3.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4 Flash accepts text; DeepSeek V4 Flash 0731 accepts text; Qwen3.5 Flash accepts text, images and video. Qwen3.5 Flash handles the widest range of inputs.
Are any of these open source?
DeepSeek V4 Flash and DeepSeek V4 Flash 0731 publishes its weights (MIT) and can be self-hosted; Qwen3.5 Flash is proprietary.
Which is newer?
DeepSeek V4 Flash 0731 is the newest, released Jul 31, 2026. DeepSeek V4 Flash came out Apr 24, 2026; Qwen3.5 Flash came out Feb 23, 2026. Knowledge cutoff: DeepSeek V4 Flash May 2025, DeepSeek V4 Flash 0731 May 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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