Compare coding-oriented model APIs by context length, tool support, JSON output, latency estimate, price, and recommended production role.
Coding model selection depends on repository size, tool-calling needs, instruction reliability, and the cost of long output. A coding assistant that reads a large codebase needs different economics from a short code-completion feature. NextModel highlights coding candidates with context length, tool support, price, and best-use guidance so teams can choose a primary model and a fallback policy.
Source basis: NextModel use-case taxonomy and OpenRouter supported-parameter metadata when available.
Fit score
Start with the shortlist, then test real prompts and compare monthly cost before production routing.
Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...
Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....
DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...
Comparison table
This table is designed for search visitors and developer teams who need a practical decision view, not a generic list of model names.
| Model | Provider | Input | Output | Context | Capabilities | Best for | Latency | Status | Source |
|---|---|---|---|---|---|---|---|---|---|
| Anthropic: Claude Opus 4.7anthropic/claude-opus-4.7 | Anthropic | $5 / 1M tokens | $25 / 1M tokens | 1M | Tool callingJSON modeLong contextReasoning | frontier reasoning, large codebase review | 2300-6800ms | Catalog | OpenRouter if available |
| Anthropic: Claude Sonnet 4.5anthropic/claude-sonnet-4.5 | Anthropic | $3 / 1M tokens | $15 / 1M tokens | 1M | Tool callingJSON modeLong contextReasoning | coding agents, code review | 1600-4800ms | Catalog | OpenRouter if available |
| DeepSeek: R1deepseek/deepseek-r1 | DeepSeek | $0.7 / 1M tokens | $2.50 / 1M tokens | 163.8k | JSON modeLong contextReasoningStreaming | Chinese reasoning, math | 1800-6000ms | Catalog | OpenRouter if available |
| DeepSeek: DeepSeek V4 Flashdeepseek/deepseek-v4-flash | DeepSeek | $0.112 / 1M tokens | $0.224 / 1M tokens | 1M | Tool callingJSON modeLong contextReasoning | low-cost Chinese tasks, long-context summary | 800-2600ms | Catalog | OpenRouter if available |
| Qwen: Qwen3 Coder Plusqwen/qwen3-coder-plus | Alibaba Cloud / Qwen | $0.65 / 1M tokens | $3.25 / 1M tokens | 1M | Tool callingJSON modeLong contextStreaming | Chinese engineering workflows, code generation | 1200-3900ms | Catalog | OpenRouter if available |
FAQ
Long context, reliable tool calling, structured output, and stable instruction following matter more than raw token price alone.
Use budget policies, compare output-heavy token cost, and route simple tasks to lower-cost models before escalating difficult tasks.