Qwen3 8B vs GPT-5.4 nano vs DeepSeek V3 0324
GPT-5.4 nano comes out ahead, 68 to 56 and 54 on our weighted score, though Qwen3 8B is 33% cheaper per token.
Alibaba (Qwen)Qwen3 8B
56/100- ECI136.2
- Price$0.18 / $0.70
- Context131K
- Our pick
OpenAIGPT-5.4 nano
68/100- ECI145.8
- Price$0.20 / $1.25
- Context400K
DeepSeekDeepSeek V3 0324
54/100- ECI135.9
- Price$0.24 / $0.90
- Context164K
GPT-5.4 nano is our pick
GPT-5.4 nano is the better all-round choice, scoring 68/100 against Qwen3 8B (56) and DeepSeek V3 0324 (54). It leads on capability, inputs & features and context window. Qwen3 8B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.4 nanoCapabilities Index (ECI): GPT-5.4 nano 145.8 · Qwen3 8B 136.2 · DeepSeek V3 0324 135.9
- Lowest priceQwen3 8BQwen3 8B $0.31 · DeepSeek V3 0324 $0.405 · GPT-5.4 nano $0.463 per 1M tokens (3:1 blend)
- Longest contextGPT-5.4 nanoGPT-5.4 nano 400,000 · DeepSeek V3 0324 163,840 · Qwen3 8B 131,072 tokens
- Widest inputsGPT-5.4 nanoQwen3 8B: Text · GPT-5.4 nano: Text, Images · DeepSeek V3 0324: Text
- Self-hostingQwen3 8B and DeepSeek V3 0324Publishes downloadable weights
| Measure | Weight | Qwen3 8B | GPT-5.4 nano | DeepSeek V3 0324 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 61 | 73 | 60 |
| Price | 25% | 74 | 66 | 68 |
| Inputs & features | 15% | 35 | 70 | 25 |
| Context window | 10% | 24 | 44 | 28 |
| Overall | 100% | 56/100 | 68/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 8BAlibaba (Qwen) | GPT-5.4 nanoOpenAI | DeepSeek V3 0324DeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 136.2 | 145.8 (best) | 135.9 |
| ECI rank | #113 of 148 | #75 of 148 (best) | #114 of 148 |
| GPQA DiamondGraduate-level science questions | 56.8% | 78.5% (best) | 67.6% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 44.9% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 56.1% | 87.8% (best) | 37.8% |
| SimpleQA VerifiedShort factual questions | — | 11.7% | — |
| Price per million tokens | |||
| Input | $0.18 (best) | $0.20 | $0.24 |
| Output | $0.70 (best) | $1.25 | $0.90 |
| Cached input | — | $0.02 | — |
| Blended (3:1) | $0.31 (best) | $0.463 | $0.405 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official OpenAI API | Median of 5 providers |
| Limits | |||
| Context window | 131,072 tokens | 400,000 tokens (best) | 163,840 tokens |
| Max output | 8,192 tokens | 128,000 tokens | 163,840 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | qwen3-8b | gpt-5.4-nano | — |
| API providers | 1 | 26 (best) | 5 |
| Released | Apr 28, 2025 | Mar 17, 2026 | Mar 24, 2025 |
| Knowledge cutoff | Apr 2025 | Aug 31, 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3 8B$3.20
- GPT-5.4 nano$4.50
- DeepSeek V3 0324$4.20
Which should you choose?
Which is better: Qwen3 8B, GPT-5.4 nano or DeepSeek V3 0324?
GPT-5.4 nano is the better all-round choice, scoring 68/100 against Qwen3 8B (56) and DeepSeek V3 0324 (54). It leads on capability, inputs & features and context window. Qwen3 8B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 8B, GPT-5.4 nano or DeepSeek V3 0324?
Qwen3 8B is cheaper at $0.18 input / $0.70 output per million tokens (official Alibaba API price). DeepSeek V3 0324 costs $0.24 input / $0.90 output per million tokens (median across 5 API providers); GPT-5.4 nano costs $0.20 input / $1.25 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.31 per million tokens for Qwen3 8B versus $0.405 for DeepSeek V3 0324 (1.3× as much) and $0.463 for GPT-5.4 nano (1.5× as much).
Which scores higher on benchmarks?
GPT-5.4 nano scores higher on the Capabilities Index (ECI): GPT-5.4 nano 145.8 (#75 of 148), Qwen3 8B 136.2 (#113 of 148) and DeepSeek V3 0324 135.9 (#114 of 148). Their confidence ranges do not overlap (143.2–147.7 vs 129.7–138.1), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-5.4 nano 78.5%, DeepSeek V3 0324 67.6%, Qwen3 8B 56.8%; OTIS Mock AIME 2024–2025 — GPT-5.4 nano 87.8%, Qwen3 8B 56.1%, DeepSeek V3 0324 37.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 8B, GPT-5.4 nano and DeepSeek V3 0324 yet, so there is no like-for-like coding score. On overall capability, GPT-5.4 nano 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?
GPT-5.4 nano has the largest context window at 400,000 tokens, against 163,840 for DeepSeek V3 0324 and 131,072 for Qwen3 8B. Maximum output per response: Qwen3 8B up to 8,192, GPT-5.4 nano up to 128,000, DeepSeek V3 0324 up to 163,840 tokens.
Which can read images, PDFs, audio or video?
Qwen3 8B accepts text; GPT-5.4 nano accepts text and images; DeepSeek V3 0324 accepts text. GPT-5.4 nano handles the widest range of inputs.
Are any of these open source?
Qwen3 8B and DeepSeek V3 0324 publishes its weights and can be self-hosted; GPT-5.4 nano is proprietary.
Which is newer?
GPT-5.4 nano is the newest, released Mar 17, 2026. Qwen3 8B came out Apr 28, 2025; DeepSeek V3 0324 came out Mar 24, 2025. Knowledge cutoff: Qwen3 8B Apr 2025, GPT-5.4 nano Aug 31, 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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