DeepSeek V4 Pro vs GLM-5V-Turbo vs Nemotron 3 Nano Omni 30B A3B Reasoning
Nemotron 3 Nano Omni 30B A3B Reasoning comes out ahead, 69 to 49 and 45 on our weighted score, and it is the cheaper option too.
DeepSeek
DeepSeek V4 Pro
45/100- ECI—
- Price$1.32 / $3.00
- Context1M
Z.ai (Zhipu)
GLM-5V-Turbo
49/100- ECI—
- Price$1.20 / $4.00
- Context200K
- Our pick
NVIDIA
Nemotron 3 Nano Omni 30B A3B Reasoning
69/100- ECI—
- Price$0.25 / $0.85
- Context256K
Nemotron 3 Nano Omni 30B A3B Reasoning is our pick
Nemotron 3 Nano Omni 30B A3B Reasoning is the better all-round choice, scoring 69/100 against GLM-5V-Turbo (49) and DeepSeek V4 Pro (45). It leads on price and inputs & features. DeepSeek V4 Pro wins on context window. 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 priceNemotron 3 Nano Omni 30B A3B ReasoningNemotron 3 Nano Omni 30B A3B Reasoning $0.40 · DeepSeek V4 Pro $1.74 · GLM-5V-Turbo $1.90 per 1M tokens (3:1 blend)
- Longest contextDeepSeek V4 ProDeepSeek V4 Pro 1,000,000 · Nemotron 3 Nano Omni 30B A3B Reasoning 256,000 · GLM-5V-Turbo 200,000 tokens
- Widest inputsGLM-5V-Turbo and Nemotron 3 Nano Omni 30B A3B ReasoningDeepSeek V4 Pro: Text · GLM-5V-Turbo: Text, Images, PDFs, Video · Nemotron 3 Nano Omni 30B A3B Reasoning: Text, Images, Audio, Video
- Self-hostingDeepSeek V4 Pro and Nemotron 3 Nano Omni 30B A3B ReasoningPublishes downloadable weights
| Measure | Weight | DeepSeek V4 Pro | GLM-5V-Turbo | Nemotron 3 Nano Omni 30B A3B Reasoning |
|---|---|---|---|---|
| Price | 50% | 38 | 37 | 69 |
| Inputs & features | 30% | 45 | 80 | 90 |
| Context window | 20% | 60 | 32 | 36 |
| Overall | 100% | 45/100 | 49/100 | 69/100 |
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) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.32 | $1.20 | $0.25 (best) |
| Output | $3.00 | $4.00 | $0.85 (best) |
| Cached input | — | $0.24 | — |
| Blended (3:1) | $1.74 | $1.90 | $0.40 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 49 providers | Official Z.AI API | Median of 4 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 200,000 tokens | 256,000 tokens |
| Max output | 384,000 tokens (best) | 131,072 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | Yes |
| Video | No | Yes | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | — | glm-5v-turbo | nvidia/nemotron-3-nano-omni-30b-a3b-reasoning |
| API providers | 52 (best) | 14 | 8 |
| Released | Apr 24, 2026 | Apr 1, 2026 | Apr 28, 2026 |
| Knowledge cutoff | 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 Pro$19.20
GLM-5V-Turbo$20.00
Nemotron 3 Nano Omni 30B A3B Reasoning$4.20
Which should you choose?
Which is better: DeepSeek V4 Pro, GLM-5V-Turbo or Nemotron 3 Nano Omni 30B A3B Reasoning?
Nemotron 3 Nano Omni 30B A3B Reasoning is the better all-round choice, scoring 69/100 against GLM-5V-Turbo (49) and DeepSeek V4 Pro (45). It leads on price and inputs & features. DeepSeek V4 Pro wins on context window. 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, GLM-5V-Turbo or Nemotron 3 Nano Omni 30B A3B Reasoning?
Nemotron 3 Nano Omni 30B A3B Reasoning is cheaper at $0.25 input / $0.85 output per million tokens (median across 4 API providers; free on Nvidia). DeepSeek V4 Pro costs $1.32 input / $3.00 output per million tokens (median across 49 API providers); GLM-5V-Turbo costs $1.20 input / $4.00 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.40 per million tokens for Nemotron 3 Nano Omni 30B A3B Reasoning versus $1.74 for DeepSeek V4 Pro (4.3× as much) and $1.90 for GLM-5V-Turbo (4.7× 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, GLM-5V-Turbo has not been scored yet and Nemotron 3 Nano Omni 30B A3B Reasoning has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4 Pro, GLM-5V-Turbo and Nemotron 3 Nano Omni 30B A3B Reasoning 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?
DeepSeek V4 Pro has the largest context window at 1,000,000 tokens, against 256,000 for Nemotron 3 Nano Omni 30B A3B Reasoning and 200,000 for GLM-5V-Turbo. Maximum output per response: DeepSeek V4 Pro up to 384,000, GLM-5V-Turbo up to 131,072, Nemotron 3 Nano Omni 30B A3B Reasoning up to 65,536 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4 Pro accepts text; GLM-5V-Turbo accepts text, images, PDFs and video; Nemotron 3 Nano Omni 30B A3B Reasoning accepts text, images, audio and video. GLM-5V-Turbo handles the widest range of inputs.
Are any of these open source?
DeepSeek V4 Pro and Nemotron 3 Nano Omni 30B A3B Reasoning publishes its weights and can be self-hosted; GLM-5V-Turbo is proprietary.
Which is newer?
Nemotron 3 Nano Omni 30B A3B Reasoning is the newest, released Apr 28, 2026. DeepSeek V4 Pro came out Apr 24, 2026; GLM-5V-Turbo came out Apr 1, 2026. Knowledge cutoff: DeepSeek V4 Pro 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.