Q1 2026 model scorecard — every frontier release ranked
Q1 2026 saw 255 model releases. Here are the ones that matter, ranked and compared.
The scorecard
| Model | Provider | SWE-bench | GPQA | Arena Elo | Input $/M | Context | Verdict |
|---|---|---|---|---|---|---|---|
| Claude Opus 4.6 | Anthropic | 80.8% | 94.3% | 1504 | $5.00 | 1M | Best reasoning quality |
| Gemini 3.1 Pro | 78.8%* | 90.8% | 1493 | $2.00 | 2M | Best value frontier | |
| GPT-5.4 | OpenAI | N/R | 92.0% | 1484 | $2.50 | 256K | Best computer-use |
| Grok 4.20 β2 | xAI | — | 86.2% | 1491 | — | — | Dark horse |
| DeepSeek V4 | DeepSeek | 72.5% | 84.0% | 1445 | $0.28 | 128K | Best price/performance |
| Llama 4 Maverick | Meta | 68.5% | 78.0% | — | Free | 10M | Best open-weight |
| Qwen 3.6 Plus | Alibaba | — | 82.0% | — | $0.30 | 1M | Best open CJK |
| Gemma 4 | — | 72.0% | — | Free | 128K | Best for consumer HW |
*Gemini 3.1 Pro leads SWE-bench among GA models. N/R = OpenAI no longer reports SWE-bench Verified.
Key takeaways
1. The pricing race to the bottom
Frontier model input pricing: Opus $5 → Gemini $2 → GPT $2.50 → DeepSeek $0.28. A year ago, $5/M was cheap. Now it’s the premium tier. DeepSeek V4 delivers 85% of frontier quality at 5% of the cost.
2. Context windows are diverging
Llama 4 at 10M tokens, Gemini at 2M, Claude at 1M, GPT at 256K, DeepSeek at 128K. If your workload needs long context (large codebase analysis, document processing, long conversations), this matters more than benchmark scores.
3. Benchmarks are breaking
OpenAI stopped reporting SWE-bench Verified scores, citing data contamination. Claude Mythos Preview (93.9%) is a research model not available via API. The gap between “benchmark performance” and “production usefulness” is widening. Arena Elo (based on human preference) is arguably the most honest metric left.
4. Open-source is closing the gap
DeepSeek V4 (1T params, $0.28/M) and Llama 4 (400B MoE, free) are within 10 points of frontier on most benchmarks. For many production workloads, the quality difference is invisible. The remaining gap is in novel reasoning, long-context coherence, and instruction following.
5. The real differentiator is ecosystem
Benchmarks converge. What matters now: context window size, tool-use quality, agentic capabilities, API ergonomics, and pricing. Claude’s 1M context + Agent SDK + Managed Agents is a different proposition than GPT-5.4’s computer-use strength, which is different from Llama 4’s self-hosting flexibility.
How to choose
Budget-constrained, high volume: DeepSeek V4 or V4 Lite
Need the best quality, cost no object: Claude Opus 4.6
Best all-around value: Gemini 3.1 Pro ($2/M, 2M context, strong benchmarks)
Self-hosting required: Llama 4 Maverick (400B MoE) or Gemma 4 (consumer hardware)
Computer-use / web automation: GPT-5.4
Building agents: Claude (Agent SDK + Managed Agents ecosystem)