DeepSeek V4 Pro vs DeepSeek V4 Pro 0813 vs Gemini 3.6 Flash
Gemini 3.6 Flash comes out ahead, 63 to 50 and 45 on our weighted score, though DeepSeek V4 Pro 0813 is 34% cheaper per token.
DeepSeek
DeepSeek V4 Pro
45/100- ECI—
- Price$1.32 / $3.00
- Context1M
DeepSeek
DeepSeek V4 Pro 0813
50/100- ECI155.4
- Price$0.66 / $1.98
- Context1M
- Our pick
Google
Gemini 3.6 Flash
63/100- ECI154.3
- Price$0.75 / $3.75
- Context1.05M
Gemini 3.6 Flash is our pick
Gemini 3.6 Flash is the better all-round choice, scoring 63/100 against DeepSeek V4 Pro 0813 (50) and DeepSeek V4 Pro (45). It leads on inputs & features. DeepSeek V4 Pro 0813 wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceDeepSeek V4 Pro 0813DeepSeek V4 Pro 0813 $0.99 · Gemini 3.6 Flash $1.50 · DeepSeek V4 Pro $1.74 per 1M tokens (3:1 blend)
- Longest contextGemini 3.6 FlashGemini 3.6 Flash 1,048,576 · DeepSeek V4 Pro 1,000,000 · DeepSeek V4 Pro 0813 1,000,000 tokens
- Widest inputsGemini 3.6 FlashDeepSeek V4 Pro: Text · DeepSeek V4 Pro 0813: Text · Gemini 3.6 Flash: Text, Images, PDFs, Audio, Video
- Self-hostingDeepSeek V4 Pro and DeepSeek V4 Pro 0813Publishes downloadable weights (MIT)
| Measure | Weight | DeepSeek V4 Pro | DeepSeek V4 Pro 0813 | Gemini 3.6 Flash |
|---|---|---|---|---|
| Price | 50% | 38 | 50 | 42 |
| Inputs & features | 30% | 45 | 45 | 100 |
| Context window | 20% | 60 | 60 | 61 |
| Overall | 100% | 45/100 | 50/100 | 63/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 155.4 (best) | 154.3 |
| ECI rank | — | #26 of 148 (best) | #34 of 148 |
| GPQA DiamondGraduate-level science questions | — | 91.7% | 94.1% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 64.6% (best) | 59.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 98.6% (best) | 94.2% |
| SimpleQA VerifiedShort factual questions | — | 52.9% | 66.2% (best) |
| Price per million tokens | |||
| Input | $1.32 | $0.66 (best) | $0.75 |
| Output | $3.00 | $1.98 (best) | $3.75 |
| Cached input | — | $0.022 (best) | $0.075 |
| Blended (3:1) | $1.74 | $0.99 (best) | $1.50 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 49 providers | Official DeepSeek API | Official Google API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,000,000 tokens | 1,048,576 tokens (best) |
| 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 | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | Yeslow · high · max | Yesminimal · low · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | OpenMIT | Proprietary |
| API model ID | — | deepseek-v4-pro | gemini-3.6-flash |
| API providers | 52 (best) | 37 | 25 |
| Released | Apr 24, 2026 | Aug 12, 2026 | Jul 21, 2026 |
| Knowledge cutoff | May 2025 | — | Mar 2026 |
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 Pro$19.20
DeepSeek V4 Pro 0813$10.56
Gemini 3.6 Flash$15.00
Which should you choose?
Which is better: DeepSeek V4 Pro, DeepSeek V4 Pro 0813 or Gemini 3.6 Flash?
Gemini 3.6 Flash is the better all-round choice, scoring 63/100 against DeepSeek V4 Pro 0813 (50) and DeepSeek V4 Pro (45). It leads on inputs & features. DeepSeek V4 Pro 0813 wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DeepSeek V4 Pro, DeepSeek V4 Pro 0813 or Gemini 3.6 Flash?
DeepSeek V4 Pro 0813 is cheaper at $0.66 input / $1.98 output per million tokens (official DeepSeek API price). Gemini 3.6 Flash costs $0.75 input / $3.75 output per million tokens (official Google API price); DeepSeek V4 Pro costs $1.32 input / $3.00 output per million tokens (median across 49 API providers). At a typical mix of three input tokens to one output token, that is $0.99 per million tokens for DeepSeek V4 Pro 0813 versus $1.50 for Gemini 3.6 Flash (1.5× as much) and $1.74 for DeepSeek V4 Pro (1.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DeepSeek V4 Pro has not been scored yet, DeepSeek V4 Pro 0813 has an ECI of 155.4 and Gemini 3.6 Flash has an ECI of 154.3.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4 Pro, DeepSeek V4 Pro 0813 and Gemini 3.6 Flash yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 3.6 Flash has the largest context window at 1,048,576 tokens, against 1,000,000 for DeepSeek V4 Pro and 1,000,000 for DeepSeek V4 Pro 0813. Maximum output per response: DeepSeek V4 Pro up to 384,000, DeepSeek V4 Pro 0813 up to 384,000, Gemini 3.6 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4 Pro accepts text; DeepSeek V4 Pro 0813 accepts text; Gemini 3.6 Flash accepts text, images, PDFs, audio and video. Gemini 3.6 Flash handles the widest range of inputs.
Are any of these open source?
DeepSeek V4 Pro and DeepSeek V4 Pro 0813 publishes its weights (MIT) and can be self-hosted; Gemini 3.6 Flash is proprietary.
Which is newer?
DeepSeek V4 Pro 0813 is the newest, released Aug 12, 2026. Gemini 3.6 Flash came out Jul 21, 2026; DeepSeek V4 Pro came out Apr 24, 2026. Knowledge cutoff: DeepSeek V4 Pro May 2025, Gemini 3.6 Flash Mar 2026.
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.