Qwen Plus Character (Japanese) vs Hermes 3 70B Instruct vs Codestral
Codestral comes out ahead, 49 to 32 and 27 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen Plus Character (Japanese)
27/100- ECI—
- Price$0.50 / $1.40
- Context8K
Nous ResearchHermes 3 70B Instruct
32/100- ECI—
- Price$0.70 / $0.70
- Context131K
- Our pick
Mistral AICodestral
49/100- ECI—
- Price$0.30 / $0.90
- Context256K
Codestral is our pick
Codestral is the better all-round choice, scoring 49/100 against Hermes 3 70B Instruct (32) and Qwen Plus Character (Japanese) (27). It leads on price, inputs & features and 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 priceCodestralCodestral $0.45 · Hermes 3 70B Instruct $0.70 · Qwen Plus Character (Japanese) $0.725 per 1M tokens (3:1 blend)
- Longest contextCodestralCodestral 256,000 · Hermes 3 70B Instruct 131,072 · Qwen Plus Character (Japanese) 8,192 tokens
- Widest inputsSame inputsQwen Plus Character (Japanese): Text · Hermes 3 70B Instruct: Text · Codestral: Text
- Self-hostingHermes 3 70B Instruct and CodestralPublishes downloadable weights
| Measure | Weight | Qwen Plus Character (Japanese) | Hermes 3 70B Instruct | Codestral |
|---|---|---|---|---|
| Price | 50% | 54 | 55 | 64 |
| Inputs & features | 30% | 0 | 0 | 35 |
| Context window | 20% | 0 | 25 | 36 |
| Overall | 100% | 27/100 | 32/100 | 49/100 |
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 | Qwen Plus Character (Japanese)Alibaba (Qwen) | Hermes 3 70B InstructNous Research | CodestralMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.70 | $0.30 (best) |
| Output | $1.40 | $0.70 (best) | $0.90 |
| Cached input | — | — | $0.03 |
| Blended (3:1) | $0.725 | $0.70 | $0.45 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 5 providers | Official Mistral API |
| Limits | |||
| Context window | 8,192 tokens | 131,072 tokens | 256,000 tokens (best) |
| Max output | 512 tokens | 16,384 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | No | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | qwen-plus-character-ja | — | codestral-latest |
| API providers | 1 | 5 (best) | 4 |
| Released | Jan 2024 | Aug 18, 2024 | May 29, 2024 |
| Knowledge cutoff | Apr 2024 | Dec 31, 2023 | Oct 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen Plus Character (Japanese)$7.80
- Hermes 3 70B Instruct$8.40
- Codestral$4.80
Which should you choose?
Which is better: Qwen Plus Character (Japanese), Hermes 3 70B Instruct or Codestral?
Codestral is the better all-round choice, scoring 49/100 against Hermes 3 70B Instruct (32) and Qwen Plus Character (Japanese) (27). It leads on price, inputs & features and 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, Qwen Plus Character (Japanese), Hermes 3 70B Instruct or Codestral?
Codestral is cheaper at $0.30 input / $0.90 output per million tokens (official Mistral API price). Hermes 3 70B Instruct costs $0.70 input / $0.70 output per million tokens (median across 5 API providers); Qwen Plus Character (Japanese) costs $0.50 input / $1.40 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.45 per million tokens for Codestral versus $0.70 for Hermes 3 70B Instruct (1.6× as much) and $0.725 for Qwen Plus Character (Japanese) (1.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen Plus Character (Japanese) has not been scored yet, Hermes 3 70B Instruct has not been scored yet and Codestral has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen Plus Character (Japanese), Hermes 3 70B Instruct and Codestral yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen Plus Character (Japanese) and Hermes 3 70B Instruct does not support tool calling, which most coding agents need.
Which has the bigger context window?
Codestral has the largest context window at 256,000 tokens, against 131,072 for Hermes 3 70B Instruct and 8,192 for Qwen Plus Character (Japanese). Maximum output per response: Qwen Plus Character (Japanese) up to 512, Hermes 3 70B Instruct up to 16,384, Codestral up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Qwen Plus Character (Japanese) accepts text; Hermes 3 70B Instruct accepts text; Codestral accepts text. They handle the same number of input types.
Are any of these open source?
Hermes 3 70B Instruct and Codestral publishes its weights and can be self-hosted; Qwen Plus Character (Japanese) is proprietary.
Which is newer?
Hermes 3 70B Instruct is the newest, released Aug 18, 2024. Codestral came out May 29, 2024; Qwen Plus Character (Japanese) came out Jan 2024. Knowledge cutoff: Qwen Plus Character (Japanese) Apr 2024, Hermes 3 70B Instruct Dec 31, 2023, Codestral Oct 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 Nov 2, 2026.
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