DeepSeek-V3 vs Qwen3 235B-A22B Instruct 2507
Qwen3 235B-A22B Instruct 2507 comes out ahead, 58 to 50 on our weighted score, and it is the cheaper option too.
DeepSeekDeepSeek-V3
50/100- ECI132.3
- Price$0.32 / $1.10
- Context131K
- Our pick
Alibaba (Qwen)Qwen3 235B-A22B Instruct 2507
58/100- ECI138.9
- Price$0.15 / $0.75
- Context262K
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Qwen3 235B-A22B Instruct 2507 is our pick
Qwen3 235B-A22B Instruct 2507 is the better all-round choice, scoring 58/100 against DeepSeek-V3 (50). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 235B-A22B Instruct 2507Capabilities Index (ECI): Qwen3 235B-A22B Instruct 2507 138.9 · DeepSeek-V3 132.3
- Lowest priceQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 $0.30 · DeepSeek-V3 $0.515 per 1M tokens (3:1 blend)
- Longest contextQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 262,144 · DeepSeek-V3 131,072 tokens
- Widest inputsSame inputsDeepSeek-V3: Text · Qwen3 235B-A22B Instruct 2507: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-V3 | Qwen3 235B-A22B Instruct 2507 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 56 | 64 |
| Price | 25% | 64 | 75 |
| Inputs & features | 15% | 25 | 25 |
| Context window | 10% | 24 | 37 |
| Overall | 100% | 50/100 | 58/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-V3DeepSeek | Qwen3 235B-A22B Instruct 2507Alibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 132.3 | 138.9 (best) |
| ECI rank | #121 of 148 | #105 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 56.5% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 15.8% | — |
| Price per million tokens | ||
| Input | $0.32 | $0.15 (best) |
| Output | $1.10 | $0.75 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.515 | $0.30 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 5 providers | Median of 11 providers |
| Limits | ||
| Context window | 131,072 tokens | 262,144 tokens (best) |
| Max output | 8,192 tokens | 16,384 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenDeepSeek Model License | OpenApache 2.0 |
| API model ID | — | — |
| API providers | 5 | 11 (best) |
| Released | Dec 26, 2024 | Jul 21, 2025 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek-V3$5.40
- Qwen3 235B-A22B Instruct 2507$3.00
Which should you choose?
Which is better: DeepSeek-V3 or Qwen3 235B-A22B Instruct 2507?
Qwen3 235B-A22B Instruct 2507 is the better all-round choice, scoring 58/100 against DeepSeek-V3 (50). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-V3 or Qwen3 235B-A22B Instruct 2507?
Qwen3 235B-A22B Instruct 2507 is cheaper at $0.15 input / $0.75 output per million tokens (median across 11 API providers). DeepSeek-V3 costs $0.32 input / $1.10 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.30 per million tokens for Qwen3 235B-A22B Instruct 2507 versus $0.515 for DeepSeek-V3 (1.7× as much).
Which scores higher on benchmarks?
Qwen3 235B-A22B Instruct 2507 scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B Instruct 2507 138.9 (#105 of 148) and DeepSeek-V3 132.3 (#121 of 148). Their confidence ranges do not overlap (135.8–140.6 vs 127.5–135.5), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-V3 and Qwen3 235B-A22B Instruct 2507 yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B Instruct 2507 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Qwen3 235B-A22B Instruct 2507 has the largest context window at 262,144 tokens, against 131,072 for DeepSeek-V3. Maximum output per response: DeepSeek-V3 up to 8,192, Qwen3 235B-A22B Instruct 2507 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-V3 accepts text; Qwen3 235B-A22B Instruct 2507 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (DeepSeek Model License and Apache 2.0), so you can self-host them.
Which is newer?
Qwen3 235B-A22B Instruct 2507 is the newest, released Jul 21, 2025. DeepSeek-V3 came out Dec 26, 2024.
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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